diff --git "a/test.txt" "b/test.txt"
new file mode 100644--- /dev/null
+++ "b/test.txt"
@@ -0,0 +1,20769 @@
+A	O
+High-Accuracy	O
+,	O
+Low-Cost	O
+Localization	O
+System	O
+for	O
+Wireless	O
+Sensor	O
+Networks	O
+ABSTRACT	O
+The	O
+problem	O
+of	O
+localization	B-KEY
+of	O
+wireless	O
+sensor	O
+nodes	O
+has	O
+long	O
+been	O
+regarded	O
+as	O
+very	O
+difficult	O
+to	O
+solve	O
+,	O
+when	O
+considering	O
+the	O
+realities	O
+of	O
+real	O
+world	O
+environments	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+formally	O
+describe	O
+,	O
+design	O
+,	O
+implement	O
+and	O
+evaluate	O
+a	O
+novel	O
+localization	B-KEY
+system	O
+,	O
+called	O
+Spotlight	O
+.	O
+Our	O
+system	O
+uses	O
+the	O
+spatio-temporal	O
+properties	O
+of	O
+well	O
+controlled	O
+events	O
+in	O
+the	O
+network	O
+-LRB-	O
+e.g.	O
+,	O
+light	O
+-RRB-	O
+,	O
+to	O
+obtain	O
+the	O
+locations	O
+of	O
+sensor	O
+nodes	O
+.	O
+We	O
+demonstrate	O
+that	O
+a	O
+high	O
+accuracy	B-KEY
+in	O
+localization	B-KEY
+can	O
+be	O
+achieved	O
+without	O
+the	O
+aid	O
+of	O
+expensive	O
+hardware	O
+on	O
+the	O
+sensor	O
+nodes	O
+,	O
+as	O
+required	O
+by	O
+other	O
+localization	B-KEY
+systems	O
+.	O
+We	O
+evaluate	O
+the	O
+performance	B-KEY
+of	O
+our	O
+system	O
+in	O
+deployments	O
+of	O
+Mica2	O
+and	O
+XSM	O
+motes	O
+.	O
+Through	O
+performance	B-KEY
+evaluations	O
+of	O
+a	O
+real	O
+system	O
+deployed	O
+outdoors	O
+,	O
+we	O
+obtain	O
+a	O
+20cm	O
+localization	B-KEY
+error	O
+.	O
+A	O
+sensor	B-KEY
+network	I-KEY
+,	O
+with	O
+any	O
+number	O
+of	O
+nodes	O
+,	O
+deployed	O
+in	O
+a	O
+2500m2	O
+area	O
+,	O
+can	O
+be	O
+localized	B-KEY
+in	O
+under	O
+10	O
+minutes	O
+,	O
+using	O
+a	O
+device	O
+that	O
+costs	O
+less	O
+than	O
+$	O
+1000	O
+.	O
+To	O
+the	O
+best	O
+of	O
+our	O
+knowledge	O
+,	O
+this	O
+is	O
+the	O
+first	O
+report	O
+of	O
+a	O
+sub-meter	O
+localization	B-KEY
+error	O
+,	O
+obtained	O
+in	O
+an	O
+outdoor	O
+environment	O
+,	O
+without	O
+equipping	O
+the	O
+wireless	O
+sensor	O
+nodes	O
+with	O
+specialized	O
+ranging	O
+hardware	O
+.	O
+
+Distributed	O
+Norm	O
+Management	O
+in	O
+Regulated	O
+Multi-Agent	O
+Systems	O
+*	O
+ABSTRACT	O
+Norms	O
+are	O
+widely	O
+recognised	O
+as	O
+a	O
+means	O
+of	O
+coordinating	B-KEY
+multi-agent	O
+systems	O
+.	O
+The	O
+distributed	O
+management	O
+of	O
+norms	O
+is	O
+a	O
+challenging	O
+issue	O
+and	O
+we	O
+observe	O
+a	O
+lack	O
+of	O
+truly	O
+distributed	O
+computational	O
+realisations	O
+of	O
+normative	O
+models	O
+.	O
+In	O
+order	O
+to	O
+regulate	O
+the	O
+behaviour	O
+of	O
+autonomous	O
+agents	O
+that	O
+take	O
+part	O
+in	O
+multiple	O
+,	O
+related	O
+activities	B-KEY
+,	O
+we	O
+propose	O
+a	O
+normative	O
+model	O
+,	O
+the	O
+Normative	B-KEY
+Structure	I-KEY
+-LRB-	O
+NS	O
+-RRB-	O
+,	O
+an	O
+artifact	O
+that	O
+is	O
+based	O
+on	O
+the	O
+propagation	O
+of	O
+normative	B-KEY
+positions	I-KEY
+-LRB-	O
+obligations	O
+,	O
+prohibitions	B-KEY
+,	O
+permissions	O
+-RRB-	O
+,	O
+as	O
+consequences	O
+of	O
+agents	O
+'	O
+actions	O
+.	O
+Within	O
+a	O
+NS	O
+,	O
+conflicts	B-KEY
+may	O
+arise	O
+due	O
+to	O
+the	O
+dynamic	O
+nature	O
+of	O
+the	O
+MAS	O
+and	O
+the	O
+concurrency	O
+of	O
+agents	O
+'	O
+actions	O
+.	O
+However	O
+,	O
+ensuring	O
+conflict-freedom	O
+of	O
+a	O
+NS	O
+at	O
+design	O
+time	O
+is	O
+computationally	O
+intractable	O
+.	O
+We	O
+show	O
+this	O
+by	O
+formalising	O
+the	O
+notion	O
+of	O
+conflict	B-KEY
+,	O
+providing	O
+a	O
+mapping	O
+of	O
+NSs	O
+into	O
+Coloured	O
+Petri	O
+Nets	O
+and	O
+borrowing	O
+well-known	O
+theoretical	O
+results	O
+from	O
+that	O
+field	O
+.	O
+Since	O
+online	O
+conflict	B-KEY
+resolution	O
+is	O
+required	O
+,	O
+we	O
+present	O
+a	O
+tractable	O
+algorithm	B-KEY
+to	O
+be	O
+employed	O
+distributedly	O
+.	O
+We	O
+then	O
+demonstrate	O
+that	O
+this	O
+algorithm	B-KEY
+is	O
+paramount	O
+for	O
+the	O
+distributed	O
+enactment	O
+of	O
+a	O
+NS	O
+.	O
+
+Interesting	B-KEY
+Nuggets	O
+and	O
+Their	O
+Impact	O
+on	O
+Definitional	O
+Question	O
+Answering	O
+ABSTRACT	O
+Current	O
+approaches	O
+to	O
+identifying	O
+definitional	O
+sentences	O
+in	O
+the	O
+context	O
+of	O
+Question	O
+Answering	O
+mainly	O
+involve	O
+the	O
+use	O
+of	O
+linguistic	O
+or	O
+syntactic	O
+patterns	O
+to	O
+identify	O
+informative	B-KEY
+nuggets	I-KEY
+.	O
+This	O
+is	O
+insufficient	O
+as	O
+they	O
+do	O
+not	O
+address	O
+the	O
+novelty	O
+factor	O
+that	O
+a	O
+definitional	O
+nugget	O
+must	O
+also	O
+possess	O
+.	O
+This	O
+paper	O
+proposes	O
+to	O
+address	O
+the	O
+deficiency	O
+by	O
+building	O
+a	O
+``	O
+Human	B-KEY
+Interest	I-KEY
+Model	O
+''	O
+from	O
+external	O
+knowledge	O
+.	O
+It	O
+is	O
+hoped	O
+that	O
+such	O
+a	O
+model	O
+will	O
+allow	O
+the	O
+computation	B-KEY
+of	I-KEY
+human	I-KEY
+interest	I-KEY
+in	O
+the	O
+sentence	O
+with	O
+respect	O
+to	O
+the	O
+topic	O
+.	O
+We	O
+compare	O
+and	O
+contrast	O
+our	O
+model	O
+with	O
+current	O
+definitional	B-KEY
+question	I-KEY
+answering	I-KEY
+models	O
+to	O
+show	O
+that	O
+interestingness	O
+plays	O
+an	O
+important	O
+factor	O
+in	O
+definitional	B-KEY
+question	I-KEY
+answering	I-KEY
+.	O
+
+Computing	O
+Good	O
+Nash	O
+Equilibria	O
+in	O
+Graphical	B-KEY
+Games	I-KEY
+*	O
+ABSTRACT	O
+This	O
+paper	O
+addresses	O
+the	O
+problem	O
+of	O
+fair	O
+equilibrium	O
+selection	O
+in	O
+graphical	B-KEY
+games	I-KEY
+.	O
+Our	O
+approach	O
+is	O
+based	O
+on	O
+the	O
+data	O
+structure	O
+called	O
+the	O
+best	O
+response	O
+policy	O
+,	O
+which	O
+was	O
+proposed	O
+by	O
+Kearns	O
+et	O
+al.	O
+-LSB-	O
+13	O
+-RSB-	O
+as	O
+a	O
+way	O
+to	O
+represent	O
+all	O
+Nash	O
+equilibria	O
+of	O
+a	O
+graphical	B-KEY
+game	I-KEY
+.	O
+In	O
+-LSB-	O
+9	O
+-RSB-	O
+,	O
+it	O
+was	O
+shown	O
+that	O
+the	O
+best	O
+response	O
+policy	O
+has	O
+polynomial	O
+size	O
+as	O
+long	O
+as	O
+the	O
+underlying	O
+graph	O
+is	O
+a	O
+path	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+show	O
+that	O
+if	O
+the	O
+underlying	O
+graph	O
+is	O
+a	O
+bounded-degree	O
+tree	O
+and	O
+the	O
+best	O
+response	O
+policy	O
+has	O
+polynomial	O
+size	O
+then	O
+there	O
+is	O
+an	O
+efficient	O
+algorithm	O
+which	O
+constructs	O
+a	O
+Nash	B-KEY
+equilibrium	I-KEY
+that	O
+guarantees	O
+certain	O
+payoffs	O
+to	O
+all	O
+participants	O
+.	O
+Another	O
+attractive	O
+solution	O
+concept	O
+is	O
+a	O
+Nash	B-KEY
+equilibrium	I-KEY
+that	O
+maximizes	O
+the	O
+social	B-KEY
+welfare	I-KEY
+.	O
+We	O
+show	O
+that	O
+,	O
+while	O
+exactly	O
+computing	O
+the	O
+latter	O
+is	O
+infeasible	O
+-LRB-	O
+we	O
+prove	O
+that	O
+solving	O
+this	O
+problem	O
+may	O
+involve	O
+algebraic	O
+numbers	O
+of	O
+an	O
+arbitrarily	O
+high	O
+degree	O
+-RRB-	O
+,	O
+there	O
+exists	O
+an	O
+FPTAS	O
+for	O
+finding	O
+such	O
+an	O
+equilibrium	O
+as	O
+long	O
+as	O
+the	O
+best	O
+response	O
+policy	O
+has	O
+polynomial	O
+size	O
+.	O
+These	O
+two	O
+algorithms	O
+can	O
+be	O
+combined	O
+to	O
+produce	O
+Nash	O
+equilibria	O
+that	O
+satisfy	O
+various	O
+fairness	O
+criteria	O
+.	O
+
+On	O
+The	O
+Complexity	O
+of	O
+Combinatorial	B-KEY
+Auctions	I-KEY
+:	O
+Structured	B-KEY
+Item	I-KEY
+Graphs	I-KEY
+and	O
+Hypertree	B-KEY
+Decompositions	I-KEY
+ABSTRACT	O
+The	O
+winner	O
+determination	O
+problem	O
+in	O
+combinatorial	B-KEY
+auctions	I-KEY
+is	O
+the	O
+problem	O
+of	O
+determining	O
+the	O
+allocation	O
+of	O
+the	O
+items	O
+among	O
+the	O
+bidders	O
+that	O
+maximizes	O
+the	O
+sum	O
+of	O
+the	O
+accepted	B-KEY
+bid	I-KEY
+prices	I-KEY
+.	O
+While	O
+this	O
+problem	O
+is	O
+in	O
+general	O
+NPhard	O
+,	O
+it	O
+is	O
+known	O
+to	O
+be	O
+feasible	O
+in	O
+polynomial	B-KEY
+time	I-KEY
+on	O
+those	O
+instances	O
+whose	O
+associated	O
+item	O
+graphs	O
+have	O
+bounded	O
+treewidth	O
+-LRB-	O
+called	O
+structured	B-KEY
+item	I-KEY
+graphs	I-KEY
+-RRB-	O
+.	O
+Formally	O
+,	O
+an	O
+item	O
+graph	O
+is	O
+a	O
+graph	O
+whose	O
+nodes	O
+are	O
+in	O
+one-to-one	O
+correspondence	O
+with	O
+items	O
+,	O
+and	O
+edges	O
+are	O
+such	O
+that	O
+for	O
+any	O
+bid	O
+,	O
+the	O
+items	O
+occurring	O
+in	O
+it	O
+induce	O
+a	O
+connected	O
+subgraph	O
+.	O
+Note	O
+that	O
+many	O
+item	O
+graphs	O
+might	O
+be	O
+associated	O
+with	O
+a	O
+given	O
+combinatorial	B-KEY
+auction	I-KEY
+,	O
+depending	O
+on	O
+the	O
+edges	O
+selected	O
+for	O
+guaranteeing	O
+the	O
+connectedness	O
+.	O
+In	O
+fact	O
+,	O
+the	O
+tractability	O
+of	O
+determining	O
+whether	O
+a	O
+structured	B-KEY
+item	I-KEY
+graph	I-KEY
+of	O
+a	O
+fixed	B-KEY
+treewidth	I-KEY
+exists	O
+-LRB-	O
+and	O
+if	O
+so	O
+,	O
+computing	O
+one	O
+-RRB-	O
+was	O
+left	O
+as	O
+a	O
+crucial	O
+open	O
+problem	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+solve	O
+this	O
+problem	O
+by	O
+proving	O
+that	O
+the	O
+existence	O
+of	O
+a	O
+structured	B-KEY
+item	I-KEY
+graph	I-KEY
+is	O
+computationally	O
+intractable	O
+,	O
+even	O
+for	O
+treewidth	O
+3	O
+.	O
+Motivated	O
+by	O
+this	O
+bad	O
+news	O
+,	O
+we	O
+investigate	O
+different	O
+kinds	O
+of	O
+structural	O
+requirements	O
+that	O
+can	O
+be	O
+used	O
+to	O
+isolate	O
+tractable	O
+classes	O
+of	O
+combinatorial	B-KEY
+auctions	I-KEY
+.	O
+We	O
+show	O
+that	O
+the	O
+notion	O
+of	O
+hypertree	B-KEY
+decomposition	I-KEY
+,	O
+a	O
+recently	O
+introduced	O
+measure	O
+of	O
+hypergraph	B-KEY
+cyclicity	O
+,	O
+turns	O
+out	O
+to	O
+be	O
+most	O
+useful	O
+here	O
+.	O
+Indeed	O
+,	O
+we	O
+show	O
+that	O
+the	O
+winner	O
+determination	O
+problem	O
+is	O
+solvable	O
+in	O
+polynomial	B-KEY
+time	I-KEY
+on	O
+instances	O
+whose	O
+bidder	O
+interactions	O
+can	O
+be	O
+represented	O
+with	O
+-LRB-	O
+dual	O
+-RRB-	O
+hypergraphs	B-KEY
+having	O
+bounded	O
+hypertree	O
+width	O
+.	O
+Even	O
+more	O
+surprisingly	O
+,	O
+we	O
+show	O
+that	O
+the	O
+class	O
+of	O
+tractable	O
+instances	O
+identified	O
+by	O
+means	O
+of	O
+our	O
+approach	O
+properly	O
+contains	O
+the	O
+class	O
+of	O
+instances	O
+having	O
+a	O
+structured	B-KEY
+item	I-KEY
+graph	I-KEY
+.	O
+
+Generalized	B-KEY
+Trade	I-KEY
+Reduction	I-KEY
+Mechanisms	O
+ABSTRACT	O
+When	O
+designing	O
+a	O
+mechanism	O
+there	O
+are	O
+several	O
+desirable	O
+properties	O
+to	O
+maintain	O
+such	O
+as	O
+incentive	O
+compatibility	O
+-LRB-	O
+IC	O
+-RRB-	O
+,	O
+individual	O
+rationality	O
+-LRB-	O
+IR	O
+-RRB-	O
+,	O
+and	O
+budget	B-KEY
+balance	I-KEY
+-LRB-	O
+BB	O
+-RRB-	O
+.	O
+It	O
+is	O
+well	O
+known	O
+-LSB-	O
+15	O
+-RSB-	O
+that	O
+it	O
+is	O
+impossible	O
+for	O
+a	O
+mechanism	O
+to	O
+maximize	O
+social	O
+welfare	O
+whilst	O
+also	O
+being	O
+IR	O
+,	O
+IC	O
+,	O
+and	O
+BB	O
+.	O
+There	O
+have	O
+been	O
+several	O
+attempts	O
+to	O
+circumvent	O
+-LSB-	O
+15	O
+-RSB-	O
+by	O
+trading	O
+welfare	O
+for	O
+BB	O
+,	O
+e.g.	O
+,	O
+in	O
+domains	O
+such	O
+as	O
+double-sided	O
+auctions	O
+-LSB-	O
+13	O
+-RSB-	O
+,	O
+distributed	O
+markets	O
+-LSB-	O
+3	O
+-RSB-	O
+and	O
+supply	O
+chain	O
+problems	O
+-LSB-	O
+2	O
+,	O
+4	O
+-RSB-	O
+.	O
+In	O
+this	O
+paper	O
+we	O
+provide	O
+a	O
+procedure	O
+called	O
+a	O
+Generalized	B-KEY
+Trade	I-KEY
+Reduction	I-KEY
+-LRB-	O
+GTR	O
+-RRB-	O
+for	O
+single-value	O
+players	O
+,	O
+which	O
+given	O
+an	O
+IR	O
+and	O
+IC	O
+mechanism	O
+,	O
+outputs	O
+a	O
+mechanism	O
+which	O
+is	O
+IR	O
+,	O
+IC	O
+and	O
+BB	O
+with	O
+a	O
+loss	O
+of	O
+welfare	O
+.	O
+We	O
+bound	O
+the	O
+welfare	O
+achieved	O
+by	O
+our	O
+procedure	O
+for	O
+a	O
+wide	O
+range	O
+of	O
+domains	O
+.	O
+In	O
+particular	O
+,	O
+our	O
+results	O
+improve	O
+on	O
+existing	O
+solutions	O
+for	O
+problems	O
+such	O
+as	O
+double	O
+sided	O
+markets	O
+with	O
+homogenous	B-KEY
+goods	I-KEY
+,	O
+distributed	O
+markets	O
+and	O
+several	O
+kinds	O
+of	O
+supply	O
+chains	O
+.	O
+Furthermore	O
+,	O
+our	O
+solution	O
+provides	O
+budget	B-KEY
+balanced	I-KEY
+mechanisms	O
+for	O
+several	O
+open	O
+problems	O
+such	O
+as	O
+combinatorial	O
+double-sided	O
+auctions	O
+and	O
+distributed	O
+markets	O
+with	O
+strategic	O
+transportation	O
+edges	O
+.	O
+
+Fast	O
+Generation	O
+of	O
+Result	O
+Snippets	O
+in	O
+Web	O
+Search	O
+ABSTRACT	O
+The	O
+presentation	O
+of	O
+query	O
+biased	O
+document	O
+snippets	O
+as	O
+part	O
+of	O
+results	O
+pages	O
+presented	O
+by	O
+search	B-KEY
+engines	I-KEY
+has	O
+become	O
+an	O
+expectation	O
+of	O
+search	B-KEY
+engine	I-KEY
+users	O
+.	O
+In	O
+this	O
+paper	O
+we	O
+explore	O
+the	O
+algorithms	O
+and	O
+data	O
+structures	O
+required	O
+as	O
+part	O
+of	O
+a	O
+search	B-KEY
+engine	I-KEY
+to	O
+allow	O
+efficient	O
+generation	O
+of	O
+query	O
+biased	O
+snippets	O
+.	O
+We	O
+begin	O
+by	O
+proposing	O
+and	O
+analysing	O
+a	O
+document	O
+compression	O
+method	O
+that	O
+reduces	O
+snippet	B-KEY
+generation	I-KEY
+time	O
+by	O
+58	O
+%	O
+over	O
+a	O
+baseline	O
+using	O
+the	O
+zlib	O
+compression	O
+library	O
+.	O
+These	O
+experiments	O
+reveal	O
+that	O
+finding	O
+documents	O
+on	O
+secondary	O
+storage	O
+dominates	O
+the	O
+total	O
+cost	O
+of	O
+generating	O
+snippets	O
+,	O
+and	O
+so	O
+caching	O
+documents	O
+in	O
+RAM	B-KEY
+is	O
+essential	O
+for	O
+a	O
+fast	O
+snippet	B-KEY
+generation	I-KEY
+process	O
+.	O
+Using	O
+simulation	O
+,	O
+we	O
+examine	O
+snippet	B-KEY
+generation	I-KEY
+performance	B-KEY
+for	O
+different	O
+size	O
+RAM	B-KEY
+caches	O
+.	O
+Finally	O
+we	O
+propose	O
+and	O
+analyse	O
+document	O
+reordering	O
+and	O
+compaction	O
+,	O
+revealing	O
+a	O
+scheme	O
+that	O
+increases	O
+the	O
+number	O
+of	O
+document	B-KEY
+cache	I-KEY
+hits	O
+with	O
+only	O
+a	O
+marginal	O
+affect	O
+on	O
+snippet	O
+quality	O
+.	O
+This	O
+scheme	O
+effectively	O
+doubles	O
+the	O
+number	O
+of	O
+documents	O
+that	O
+can	O
+fit	O
+in	O
+a	O
+fixed	O
+size	O
+cache	O
+.	O
+
+Deployment	O
+Issues	O
+of	O
+a	O
+VoIP	B-KEY
+Conferencing	O
+System	O
+in	O
+a	O
+Virtual	O
+Conferencing	O
+Environment	O
+ABSTRACT	O
+Real-time	O
+services	O
+have	O
+been	O
+supported	O
+by	O
+and	O
+large	O
+on	O
+circuitswitched	O
+networks	O
+.	O
+Recent	O
+trends	O
+favour	O
+services	O
+ported	O
+on	O
+packet-switched	B-KEY
+networks	I-KEY
+.	O
+For	O
+audio	O
+conferencing	O
+,	O
+we	O
+need	O
+to	O
+consider	O
+many	O
+issues	O
+--	O
+scalability	O
+,	O
+quality	O
+of	O
+the	O
+conference	O
+application	O
+,	O
+floor	O
+control	O
+and	O
+load	O
+on	O
+the	O
+clients/servers	O
+--	O
+to	O
+name	O
+a	O
+few	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+describe	O
+an	O
+audio	B-KEY
+service	I-KEY
+framework	I-KEY
+designed	O
+to	O
+provide	O
+a	O
+Virtual	B-KEY
+Conferencing	I-KEY
+Environment	I-KEY
+-LRB-	O
+VCE	B-KEY
+-RRB-	O
+.	O
+The	O
+system	O
+is	O
+designed	O
+to	O
+accommodate	O
+a	O
+large	O
+number	O
+of	O
+end	O
+users	O
+speaking	O
+at	O
+the	O
+same	O
+time	O
+and	O
+spread	O
+across	O
+the	O
+Internet	O
+.	O
+The	O
+framework	O
+is	O
+based	O
+on	O
+Conference	B-KEY
+Servers	I-KEY
+-LSB-	O
+14	O
+-RSB-	O
+,	O
+which	O
+facilitate	O
+the	O
+audio	O
+handling	O
+,	O
+while	O
+we	O
+exploit	O
+the	O
+SIP	B-KEY
+capabilities	O
+for	O
+signaling	O
+purposes	O
+.	O
+Client	O
+selection	O
+is	O
+based	O
+on	O
+a	O
+recent	O
+quantifier	O
+called	O
+``	O
+Loudness	B-KEY
+Number	I-KEY
+''	O
+that	O
+helps	O
+mimic	O
+a	O
+physical	O
+face-to-face	O
+conference	O
+.	O
+We	O
+deal	O
+with	O
+deployment	O
+issues	O
+of	O
+the	O
+proposed	O
+solution	O
+both	O
+in	O
+terms	O
+of	O
+scalability	O
+and	O
+interactivity	O
+,	O
+while	O
+explaining	O
+the	O
+techniques	O
+we	O
+use	O
+to	O
+reduce	O
+the	O
+traffic	O
+.	O
+We	O
+have	O
+implemented	O
+a	O
+Conference	B-KEY
+Server	I-KEY
+-LRB-	O
+CS	O
+-RRB-	O
+application	O
+on	O
+a	O
+campus-wide	O
+network	O
+at	O
+our	O
+Institute	O
+.	O
+
+Intra-flow	O
+Loss	B-KEY
+Recovery	I-KEY
+and	I-KEY
+Control	I-KEY
+for	O
+ABSTRACT	O
+``	O
+Best	O
+effort	O
+''	O
+packet-switched	O
+networks	O
+,	O
+like	O
+the	O
+Internet	O
+,	O
+do	O
+not	O
+offer	O
+a	O
+reliable	O
+transmission	O
+of	O
+packets	O
+to	O
+applications	O
+with	O
+real-time	O
+constraints	O
+such	O
+voice	O
+.	O
+Thus	O
+,	O
+the	O
+loss	O
+of	O
+packets	O
+impairs	O
+the	O
+application-level	O
+utility	O
+.	O
+For	O
+voice	O
+this	O
+utility	O
+impairment	O
+is	O
+twofold	O
+:	O
+on	O
+one	O
+hand	O
+,	O
+even	O
+short	O
+bursts	O
+of	O
+lost	O
+packets	O
+may	O
+decrease	O
+significantly	O
+the	O
+ability	O
+of	O
+the	O
+receiver	O
+to	O
+conceal	O
+the	O
+packet	O
+loss	O
+and	O
+the	O
+speech	O
+signal	O
+out	O
+is	O
+interrupted	O
+.	O
+On	O
+the	O
+other	O
+hand	O
+,	O
+some	O
+packets	O
+may	O
+be	O
+particular	O
+sensitive	O
+to	O
+loss	O
+as	O
+they	O
+carry	O
+more	O
+important	O
+information	O
+in	O
+terms	O
+of	O
+user	O
+perception	O
+than	O
+other	O
+packets	O
+.	O
+We	O
+first	O
+develop	O
+an	O
+end-to-end	B-KEY
+model	I-KEY
+based	O
+on	O
+loss	O
+lengths	O
+with	O
+which	O
+we	O
+can	O
+describe	O
+the	O
+loss	O
+distribution	O
+within	O
+a	O
+These	O
+packet-level	B-KEY
+metrics	I-KEY
+are	O
+then	O
+linked	O
+to	O
+user-level	O
+objective	O
+speech	O
+quality	O
+metrics	O
+.	O
+Using	O
+this	O
+framework	O
+,	O
+we	O
+find	O
+that	O
+for	O
+low-compressing	O
+sample-based	O
+codecs	O
+-LRB-	O
+PCM	O
+-RRB-	O
+with	O
+loss	B-KEY
+concealment	I-KEY
+isolated	O
+packet	O
+losses	O
+can	O
+be	O
+concealed	O
+well	O
+,	O
+whereas	O
+burst	O
+losses	O
+have	O
+a	O
+higher	O
+perceptual	O
+impact	O
+.	O
+For	O
+high-compressing	O
+frame-based	O
+codecs	O
+-LRB-	O
+G.	O
+729	O
+-RRB-	O
+on	O
+one	O
+hand	O
+the	O
+impact	O
+of	O
+loss	O
+is	O
+amplified	O
+through	O
+error	O
+propagation	O
+caused	O
+by	O
+the	O
+decoder	O
+filter	O
+memories	O
+,	O
+though	O
+on	O
+the	O
+other	O
+hand	O
+such	O
+coding	O
+schemes	O
+help	O
+to	O
+perform	O
+loss	B-KEY
+concealment	I-KEY
+by	O
+extrapolation	O
+of	O
+decoder	O
+state	O
+.	O
+Contrary	O
+to	O
+sample-based	O
+codecs	O
+we	O
+show	O
+that	O
+the	O
+concealment	O
+performance	O
+may	O
+``	O
+break	O
+''	O
+at	O
+transitions	O
+within	O
+the	O
+speech	O
+signal	O
+however	O
+.	O
+We	O
+then	O
+propose	O
+mechanisms	O
+which	O
+differentiate	O
+between	O
+packets	O
+within	O
+a	O
+voice	O
+data	O
+to	O
+minimize	O
+the	O
+impact	O
+of	O
+packet	O
+loss	O
+.	O
+We	O
+designate	O
+these	O
+methods	O
+as	O
+loss	B-KEY
+recovery	I-KEY
+and	I-KEY
+control	I-KEY
+.	O
+At	O
+the	O
+end-to-end	O
+level	O
+,	O
+identification	O
+of	O
+packets	O
+sensitive	O
+to	O
+loss	O
+-LRB-	O
+sender	O
+-RRB-	O
+as	O
+well	O
+as	O
+loss	B-KEY
+concealment	I-KEY
+-LRB-	O
+receiver	O
+-RRB-	O
+takes	O
+place	O
+.	O
+Hop-by-hop	O
+support	O
+schemes	O
+then	O
+allow	O
+to	O
+-LRB-	O
+statistically	O
+-RRB-	O
+trade	O
+the	O
+loss	O
+of	O
+one	O
+packet	O
+,	O
+which	O
+is	O
+considered	O
+more	O
+important	O
+,	O
+against	O
+another	O
+one	O
+of	O
+the	O
+same	O
+flow	O
+which	O
+is	O
+of	O
+lower	O
+importance	O
+.	O
+As	O
+both	O
+ets	O
+require	O
+the	O
+same	O
+cost	O
+in	O
+terms	O
+of	O
+network	O
+transmission	O
+,	O
+a	O
+gain	O
+in	O
+user	O
+perception	O
+is	O
+obtainable	O
+.	O
+We	O
+show	O
+that	O
+significant	O
+speech	O
+quality	O
+improvements	O
+can	O
+be	O
+achieved	O
+and	O
+additional	O
+data	O
+and	O
+delay	O
+overhead	O
+can	O
+be	O
+avoided	O
+while	O
+still	O
+maintaining	O
+a	O
+network	O
+service	O
+which	O
+is	O
+virtually	O
+identical	O
+to	O
+best	O
+effort	O
+in	O
+the	O
+long	O
+term	O
+.	O
+
+Estimation	O
+and	O
+Use	O
+of	O
+Uncertainty	O
+in	O
+Pseudo-relevance	B-KEY
+Feedback	I-KEY
+ABSTRACT	O
+Existing	O
+pseudo-relevance	B-KEY
+feedback	I-KEY
+methods	O
+typically	O
+perform	O
+averaging	O
+over	O
+the	O
+top-retrieved	O
+documents	O
+,	O
+but	O
+ignore	O
+an	O
+important	O
+statistical	O
+dimension	O
+:	O
+the	O
+risk	O
+or	O
+variance	O
+associated	O
+with	O
+either	O
+the	O
+individual	O
+document	O
+models	O
+,	O
+or	O
+their	O
+combination	O
+.	O
+Treating	O
+the	O
+baseline	O
+feedback	B-KEY
+method	I-KEY
+as	O
+a	O
+black	O
+box	O
+,	O
+and	O
+the	O
+output	O
+feedback	B-KEY
+model	I-KEY
+as	O
+a	O
+random	O
+variable	O
+,	O
+we	O
+estimate	O
+a	O
+posterior	B-KEY
+distribution	I-KEY
+for	O
+the	O
+feedback	B-KEY
+model	I-KEY
+by	O
+resampling	O
+a	O
+given	O
+query	O
+'s	O
+top-retrieved	O
+documents	O
+,	O
+using	O
+the	O
+posterior	O
+mean	O
+or	O
+mode	O
+as	O
+the	O
+enhanced	B-KEY
+feedback	I-KEY
+model	I-KEY
+.	O
+We	O
+then	O
+perform	O
+model	O
+combination	O
+over	O
+several	O
+enhanced	O
+models	O
+,	O
+each	O
+based	O
+on	O
+a	O
+slightly	O
+modified	O
+query	O
+sampled	O
+from	O
+the	O
+original	O
+query	O
+.	O
+We	O
+find	O
+that	O
+resampling	O
+documents	O
+helps	O
+increase	O
+individual	O
+feedback	B-KEY
+model	I-KEY
+precision	O
+by	O
+removing	O
+noise	O
+terms	O
+,	O
+while	O
+sampling	O
+from	O
+the	O
+query	O
+improves	O
+robustness	O
+-LRB-	O
+worst-case	O
+performance	O
+-RRB-	O
+by	O
+emphasizing	O
+terms	O
+related	O
+to	O
+multiple	O
+query	O
+aspects	O
+.	O
+The	O
+result	O
+is	O
+a	O
+meta-feedback	O
+algorithm	O
+that	O
+is	O
+both	O
+more	O
+robust	O
+and	O
+more	O
+precise	O
+than	O
+the	O
+original	O
+strong	O
+baseline	O
+method	O
+.	O
+
+Pruning	B-KEY
+Policies	O
+for	O
+Two-Tiered	O
+Inverted	B-KEY
+Index	I-KEY
+with	O
+Correctness	B-KEY
+Guarantee	I-KEY
+ABSTRACT	O
+The	O
+Web	B-KEY
+search	I-KEY
+engines	I-KEY
+maintain	O
+large-scale	O
+inverted	B-KEY
+indexes	I-KEY
+which	O
+are	O
+queried	O
+thousands	O
+of	O
+times	O
+per	O
+second	O
+by	O
+users	O
+eager	O
+for	O
+information	O
+.	O
+In	O
+order	O
+to	O
+cope	O
+with	O
+the	O
+vast	O
+amounts	O
+of	O
+query	B-KEY
+loads	I-KEY
+,	O
+search	O
+engines	O
+prune	B-KEY
+their	O
+index	O
+to	O
+keep	O
+documents	O
+that	O
+are	O
+likely	O
+to	O
+be	O
+returned	O
+as	O
+top	O
+results	O
+,	O
+and	O
+use	O
+this	O
+pruned	B-KEY
+index	O
+to	O
+compute	O
+the	O
+first	O
+batches	O
+of	O
+results	O
+.	O
+While	O
+this	O
+approach	O
+can	O
+improve	O
+performance	O
+by	O
+reducing	O
+the	O
+size	O
+of	O
+the	O
+index	O
+,	O
+if	O
+we	O
+compute	O
+the	O
+top	O
+results	O
+only	O
+from	O
+the	O
+pruned	B-KEY
+index	O
+we	O
+may	O
+notice	O
+a	O
+significant	O
+degradation	O
+in	O
+the	O
+result	O
+quality	O
+:	O
+if	O
+a	O
+document	O
+should	O
+be	O
+in	O
+the	O
+top	O
+results	O
+but	O
+was	O
+not	O
+included	O
+in	O
+the	O
+pruned	O
+index	O
+,	O
+it	O
+will	O
+be	O
+placed	O
+behind	O
+the	O
+results	O
+computed	O
+from	O
+the	O
+pruned	O
+index	O
+.	O
+Given	O
+the	O
+fierce	O
+competition	O
+in	O
+the	O
+online	B-KEY
+search	I-KEY
+market	I-KEY
+,	O
+this	O
+phenomenon	O
+is	O
+clearly	O
+undesirable	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+study	O
+how	O
+we	O
+can	O
+avoid	O
+any	O
+degradation	B-KEY
+of	I-KEY
+result	I-KEY
+quality	I-KEY
+due	O
+to	O
+the	O
+pruning-based	O
+performance	O
+optimization	O
+,	O
+while	O
+still	O
+realizing	O
+most	O
+of	O
+its	O
+benefit	O
+.	O
+Our	O
+contribution	O
+is	O
+a	O
+number	O
+of	O
+modifications	O
+in	O
+the	O
+pruning	B-KEY
+techniques	O
+for	O
+creating	O
+the	O
+pruned	O
+index	O
+and	O
+a	O
+new	O
+result	O
+computation	O
+algorithm	O
+that	O
+guarantees	O
+that	O
+the	O
+top-matching	O
+pages	O
+are	O
+always	O
+placed	O
+at	O
+the	O
+top	O
+search	O
+results	O
+,	O
+even	O
+though	O
+we	O
+are	O
+computing	O
+the	O
+first	O
+batch	O
+from	O
+the	O
+pruned	O
+index	O
+most	O
+of	O
+the	O
+time	O
+.	O
+We	O
+also	O
+show	O
+how	O
+to	O
+determine	O
+the	O
+optimal	B-KEY
+size	I-KEY
+of	O
+a	O
+pruned	B-KEY
+index	O
+and	O
+we	O
+experimentally	O
+evaluate	O
+our	O
+algorithms	O
+on	O
+a	O
+collection	O
+of	O
+130	O
+million	O
+Web	O
+pages	O
+.	O
+
+Budget	B-KEY
+Optimization	I-KEY
+in	O
+Search-Based	O
+Advertising	O
+Auctions	O
+ABSTRACT	O
+Internet	B-KEY
+search	O
+companies	O
+sell	O
+advertisement	B-KEY
+slots	O
+based	O
+on	O
+users	O
+'	O
+search	O
+queries	O
+via	O
+an	O
+auction	B-KEY
+.	O
+While	O
+there	O
+has	O
+been	O
+previous	O
+work	O
+on	O
+the	O
+auction	B-KEY
+process	O
+and	O
+its	O
+game-theoretic	O
+aspects	O
+,	O
+most	O
+of	O
+it	O
+focuses	O
+on	O
+the	O
+Internet	B-KEY
+company	O
+.	O
+In	O
+this	O
+work	O
+,	O
+we	O
+focus	O
+on	O
+the	O
+advertisers	B-KEY
+,	O
+who	O
+must	O
+solve	O
+a	O
+complex	O
+optimization	B-KEY
+problem	O
+to	O
+decide	O
+how	O
+to	O
+place	O
+bids	B-KEY
+on	O
+keywords	B-KEY
+to	O
+maximize	O
+their	O
+return	O
+-LRB-	O
+the	O
+number	O
+of	O
+user	O
+clicks	O
+on	O
+their	O
+ads	O
+-RRB-	O
+for	O
+a	O
+given	O
+budget	O
+.	O
+We	O
+model	O
+the	O
+entire	O
+process	O
+and	O
+study	O
+this	O
+budget	B-KEY
+optimization	I-KEY
+problem	O
+.	O
+While	O
+most	O
+variants	O
+are	O
+NP-hard	O
+,	O
+we	O
+show	O
+,	O
+perhaps	O
+surprisingly	O
+,	O
+that	O
+simply	O
+randomizing	O
+between	O
+two	O
+uniform	O
+strategies	O
+that	O
+bid	B-KEY
+equally	O
+on	O
+all	O
+the	O
+keywords	B-KEY
+works	O
+well	O
+.	O
+More	O
+precisely	O
+,	O
+this	O
+strategy	O
+gets	O
+at	O
+least	O
+a	O
+1	O
+−	O
+1/e	O
+fraction	O
+of	O
+the	O
+maximum	O
+clicks	O
+possible	O
+.	O
+As	O
+our	O
+preliminary	O
+experiments	O
+show	O
+,	O
+such	O
+uniform	O
+strategies	O
+are	O
+likely	O
+to	O
+be	O
+practical	O
+.	O
+We	O
+also	O
+present	O
+inapproximability	O
+results	O
+,	O
+and	O
+optimal	B-KEY
+algorithms	O
+for	O
+variants	O
+of	O
+the	O
+budget	B-KEY
+optimization	I-KEY
+problem	O
+.	O
+
+Term	O
+Feedback	O
+for	O
+Information	B-KEY
+Retrieval	I-KEY
+with	O
+Language	B-KEY
+Models	I-KEY
+ABSTRACT	O
+I	O
+n	O
+t	O
+hi	O
+s	O
+paper	O
+w	O
+e	O
+s	O
+t	O
+udy	O
+t	O
+er	O
+m	O
+-	O
+based	O
+f	O
+eedback	O
+f	O
+or	O
+i	O
+nf	O
+or	O
+mat	O
+i	O
+on	O
+r	O
+etrieval	O
+in	O
+the	O
+language	B-KEY
+modeling	I-KEY
+approach	O
+.	O
+With	O
+term	O
+feedback	O
+a	O
+user	O
+directly	O
+judges	O
+the	O
+relevance	O
+of	O
+individual	O
+terms	O
+without	O
+interaction	O
+with	O
+feedback	O
+documents	O
+,	O
+taking	O
+full	O
+control	O
+of	O
+the	O
+query	B-KEY
+expansion	I-KEY
+process	O
+.	O
+We	O
+propose	O
+a	O
+cluster-based	O
+method	O
+for	O
+selecting	O
+terms	O
+to	O
+present	O
+to	O
+the	O
+user	O
+for	O
+judgment	O
+,	O
+as	O
+well	O
+as	O
+effective	O
+algorithms	O
+for	O
+constructing	O
+refined	O
+query	O
+language	B-KEY
+models	I-KEY
+from	O
+user	O
+term	O
+feedback	O
+.	O
+Our	O
+algorithms	O
+are	O
+shown	O
+to	O
+bring	O
+significant	O
+improvement	O
+in	O
+retrieval	O
+accuracy	O
+over	O
+a	O
+non-feedback	O
+baseline	O
+,	O
+and	O
+achieve	O
+comparable	O
+performance	O
+to	O
+relevance	O
+feedback	O
+.	O
+They	O
+are	O
+helpful	O
+even	O
+when	O
+there	O
+are	O
+no	O
+relevant	O
+documents	O
+in	O
+the	O
+top	O
+.	O
+
+Towards	O
+Self-organising	B-KEY
+Agent-based	O
+Resource	O
+Allocation	O
+in	O
+a	O
+Multi-Server	O
+Environment	O
+ABSTRACT	O
+Distributed	O
+applications	O
+require	O
+distributed	O
+techniques	O
+for	O
+efficient	O
+resource	B-KEY
+allocation	I-KEY
+.	O
+These	O
+techniques	O
+need	O
+to	O
+take	O
+into	O
+account	O
+the	O
+heterogeneity	O
+and	O
+potential	O
+unreliability	O
+of	O
+resources	O
+and	O
+resource	O
+consumers	O
+in	O
+a	O
+distributed	O
+environments	O
+.	O
+In	O
+this	O
+paper	O
+we	O
+propose	O
+a	O
+distributed	B-KEY
+algorithm	I-KEY
+that	O
+solves	O
+the	O
+resource	B-KEY
+allocation	I-KEY
+problem	O
+in	O
+distributed	O
+multiagent	O
+systems	O
+.	O
+Our	O
+solution	O
+is	O
+based	O
+on	O
+the	O
+self-organisation	B-KEY
+of	O
+agents	B-KEY
+,	O
+which	O
+does	O
+not	O
+require	O
+any	O
+facilitator	O
+or	O
+management	O
+layer	O
+.	O
+The	O
+resource	B-KEY
+allocation	I-KEY
+in	O
+the	O
+system	O
+is	O
+a	O
+purely	O
+emergent	O
+effect	O
+.	O
+We	O
+present	O
+results	O
+of	O
+the	O
+proposed	O
+resource	B-KEY
+allocation	I-KEY
+mechanism	O
+in	O
+the	O
+simulated	O
+static	O
+and	O
+dynamic	O
+multi-server	O
+environment	O
+.	O
+
+Realistic	O
+Cognitive	O
+Load	O
+Modeling	O
+for	O
+Enhancing	O
+Shared	O
+Mental	O
+Models	O
+in	O
+Human-Agent	O
+Collaboration	B-KEY
+ABSTRACT	O
+Human	O
+team	O
+members	O
+often	O
+develop	O
+shared	O
+expectations	B-KEY
+to	O
+predict	O
+each	O
+other	O
+'s	O
+needs	O
+and	O
+coordinate	O
+their	O
+behaviors	O
+.	O
+In	O
+this	O
+paper	O
+the	O
+concept	O
+``	O
+Shared	B-KEY
+Belief	I-KEY
+Map	I-KEY
+''	O
+is	O
+proposed	O
+as	O
+a	O
+basis	O
+for	O
+developing	O
+realistic	O
+shared	O
+expectations	B-KEY
+among	O
+a	O
+team	O
+of	O
+Human-Agent-Pairs	O
+-LRB-	O
+HAPs	O
+-RRB-	O
+.	O
+The	O
+establishment	O
+of	O
+shared	B-KEY
+belief	I-KEY
+maps	I-KEY
+relies	O
+on	O
+inter-agent	O
+information	O
+sharing	O
+,	O
+the	O
+effectiveness	O
+of	O
+which	O
+highly	O
+depends	O
+on	O
+agents	O
+'	O
+processing	O
+loads	O
+and	O
+the	O
+instantaneous	O
+cognitive	O
+loads	O
+of	O
+their	O
+human	O
+partners	O
+.	O
+We	O
+investigate	O
+HMM-based	O
+cognitive	O
+load	O
+models	O
+to	O
+facilitate	O
+team	O
+members	O
+to	O
+``	O
+share	O
+the	O
+right	O
+information	O
+with	O
+the	O
+right	O
+party	O
+at	O
+the	O
+right	O
+time	O
+''	O
+.	O
+The	O
+shared	B-KEY
+belief	I-KEY
+map	I-KEY
+concept	O
+and	O
+the	O
+cognitive/processing	O
+load	O
+models	O
+have	O
+been	O
+implemented	O
+in	O
+a	O
+cognitive	O
+agent	O
+architecture	O
+--	O
+SMMall	O
+.	O
+A	O
+series	O
+of	O
+experiments	O
+were	O
+conducted	O
+to	O
+evaluate	O
+the	O
+concept	O
+,	O
+the	O
+models	O
+,	O
+and	O
+their	O
+impacts	O
+on	O
+the	O
+evolving	O
+of	O
+shared	O
+mental	O
+models	O
+of	O
+HAP	O
+teams	O
+.	O
+
+Service	B-KEY
+Interface	I-KEY
+:	O
+A	O
+New	O
+Abstraction	O
+for	O
+Implementing	O
+and	O
+Composing	O
+Protocols	O
+*	O
+ABSTRACT	O
+In	O
+this	O
+paper	O
+we	O
+compare	O
+two	O
+approaches	O
+to	O
+the	O
+design	O
+of	O
+protocol	B-KEY
+frameworks	I-KEY
+--	O
+tools	O
+for	O
+implementing	O
+modular	B-KEY
+network	B-KEY
+protocols	O
+.	O
+The	O
+most	O
+common	O
+approach	O
+uses	O
+events	O
+as	O
+the	O
+main	O
+abstraction	O
+for	O
+a	O
+local	O
+interaction	O
+between	O
+protocol	O
+modules	B-KEY
+.	O
+We	O
+argue	O
+that	O
+an	O
+alternative	O
+approach	O
+,	O
+that	O
+is	O
+based	O
+on	O
+service	O
+abstraction	O
+,	O
+is	O
+more	O
+suitable	O
+for	O
+expressing	O
+modular	B-KEY
+protocols	O
+.	O
+It	O
+also	O
+facilitates	O
+advanced	O
+features	O
+in	O
+the	O
+design	O
+of	O
+protocols	O
+,	O
+such	O
+as	O
+dynamic	O
+update	O
+of	O
+distributed	O
+protocols	O
+.	O
+We	O
+then	O
+describe	O
+an	O
+experimental	O
+implementation	O
+of	O
+a	O
+service-based	O
+protocol	B-KEY
+framework	I-KEY
+in	O
+Java	O
+.	O
+
+A	O
+Formal	O
+Road	O
+from	O
+Institutional	B-KEY
+Norms	O
+to	O
+Organizational	O
+Structures	O
+ABSTRACT	O
+Up	O
+to	O
+now	O
+,	O
+the	O
+way	O
+institutions	B-KEY
+and	O
+organizations	O
+have	O
+been	O
+used	O
+in	O
+the	O
+development	O
+of	O
+open	O
+systems	O
+has	O
+not	O
+often	O
+gone	O
+further	O
+than	O
+a	O
+useful	O
+heuristics	O
+.	O
+In	O
+order	O
+to	O
+develop	O
+systems	O
+actually	O
+implementing	O
+institutions	B-KEY
+and	O
+organizations	O
+,	O
+formal	B-KEY
+methods	I-KEY
+should	O
+take	O
+the	O
+place	O
+of	O
+heuristic	O
+ones	O
+.	O
+The	O
+paper	O
+presents	O
+a	O
+formal	O
+semantics	O
+for	O
+the	O
+notion	O
+of	O
+institution	B-KEY
+and	O
+its	O
+components	O
+-LRB-	O
+abstract	O
+and	O
+concrete	O
+norms	B-KEY
+,	O
+empowerment	O
+of	O
+agents	O
+,	O
+roles	B-KEY
+-RRB-	O
+and	O
+defines	O
+a	O
+formal	O
+relation	O
+between	O
+institutions	B-KEY
+and	O
+organizational	B-KEY
+structures	I-KEY
+.	O
+As	O
+a	O
+result	O
+,	O
+it	O
+is	O
+shown	O
+how	O
+institutional	B-KEY
+norms	O
+can	O
+be	O
+refined	O
+to	O
+constructs	O
+--	O
+organizational	O
+structures	O
+--	O
+which	O
+are	O
+closer	O
+to	O
+an	O
+implemented	O
+system	O
+.	O
+It	O
+is	O
+also	O
+shown	O
+how	O
+such	O
+a	O
+refinement	O
+process	O
+can	O
+be	O
+fully	O
+formalized	O
+and	O
+it	O
+is	O
+therefore	O
+amenable	O
+to	O
+rigorous	O
+verification	O
+.	O
+
+Approximately-Strategyproof	O
+and	O
+Tractable	O
+Multi-Unit	O
+Auctions	O
+ABSTRACT	O
+We	O
+present	O
+an	O
+approximately-efficient	O
+and	O
+approximatelystrategyproof	O
+auction	O
+mechanism	O
+for	O
+a	O
+single-good	O
+multi-unit	O
+allocation	O
+problem	O
+.	O
+The	O
+bidding	B-KEY
+language	I-KEY
+in	O
+our	O
+auctions	O
+allows	O
+marginal-decreasing	O
+piecewise	O
+constant	O
+curves	O
+.	O
+First	O
+,	O
+we	O
+develop	O
+a	O
+fully	O
+polynomial-time	O
+approximation	O
+scheme	O
+for	O
+the	O
+multi-unit	O
+allocation	O
+problem	O
+,	O
+which	O
+computes	O
+a	O
+-LRB-	O
+1	O
++	O
+e	O
+-RRB-	O
+approximation	O
+in	O
+worst-case	O
+time	O
+T	O
+=	O
+O	O
+-LRB-	O
+n3/e	O
+-RRB-	O
+,	O
+given	O
+n	O
+bids	O
+each	O
+with	O
+a	O
+constant	O
+number	O
+of	O
+pieces	O
+.	O
+Second	O
+,	O
+we	O
+embed	O
+this	O
+approximation	O
+scheme	O
+within	O
+a	O
+Vickrey-Clarke-Groves	O
+-LRB-	O
+VCG	O
+-RRB-	O
+mechanism	O
+and	O
+compute	O
+payments	O
+to	O
+n	O
+agents	O
+for	O
+an	O
+asymptotic	O
+cost	O
+of	O
+O	O
+-LRB-	O
+T	O
+log	O
+n	O
+-RRB-	O
+.	O
+The	O
+maximal	O
+possible	O
+gain	O
+from	O
+manipulation	O
+to	O
+a	O
+bidder	O
+in	O
+the	O
+combined	O
+scheme	O
+is	O
+bounded	O
+by	O
+e	O
+/	O
+-LRB-	O
+1	O
++	O
+e	O
+-RRB-	O
+V	O
+,	O
+where	O
+V	O
+is	O
+the	O
+total	O
+surplus	O
+in	O
+the	O
+efficient	O
+outcome	O
+.	O
+
+BuddyCache	B-KEY
+:	O
+High-Performance	O
+Object	O
+Storage	O
+for	O
+Collaborative	B-KEY
+Strong-Consistency	I-KEY
+Applications	I-KEY
+in	O
+a	O
+WAN	O
+*	O
+ABSTRACT	O
+Collaborative	O
+applications	O
+provide	O
+a	O
+shared	O
+work	O
+environment	O
+for	O
+groups	O
+of	O
+networked	O
+clients	O
+collaborating	O
+on	O
+a	O
+common	O
+task	O
+.	O
+They	O
+require	O
+strong	O
+consistency	O
+for	O
+shared	O
+persistent	O
+data	O
+and	O
+efficient	O
+access	O
+to	O
+fine-grained	O
+objects	O
+.	O
+These	O
+properties	O
+are	O
+difficult	O
+to	O
+provide	O
+in	O
+wide-area	B-KEY
+networks	I-KEY
+because	O
+of	O
+high	O
+network	O
+latency	O
+.	O
+BuddyCache	B-KEY
+is	O
+a	O
+new	O
+transactional	B-KEY
+caching	O
+approach	O
+that	O
+improves	O
+the	O
+latency	O
+of	O
+access	O
+to	O
+shared	O
+persistent	O
+objects	O
+for	O
+collaborative	B-KEY
+strong-consistency	I-KEY
+applications	I-KEY
+in	O
+high-latency	O
+network	O
+environments	O
+.	O
+The	O
+challenge	O
+is	O
+to	O
+improve	O
+performance	O
+while	O
+providing	O
+the	O
+correctness	O
+and	O
+availability	O
+properties	O
+of	O
+a	O
+transactional	B-KEY
+caching	O
+protocol	O
+in	O
+the	O
+presence	O
+of	O
+node	O
+failures	O
+and	O
+slow	O
+peers	O
+.	O
+We	O
+have	O
+implemented	O
+a	O
+BuddyCache	B-KEY
+prototype	O
+and	O
+evaluated	O
+its	O
+performance	O
+.	O
+Analytical	O
+results	O
+,	O
+confirmed	O
+by	O
+measurements	O
+of	O
+the	O
+BuddyCache	B-KEY
+prototype	O
+using	O
+the	O
+multiuser	O
+007	O
+benchmark	O
+indicate	O
+that	O
+for	O
+typical	O
+Internet	O
+latencies	O
+,	O
+e.g.	O
+ranging	O
+from	O
+40	O
+to	O
+80	O
+milliseconds	O
+round	O
+trip	O
+time	O
+to	O
+the	O
+storage	O
+server	O
+,	O
+peers	O
+using	O
+BuddyCache	B-KEY
+can	O
+reduce	O
+by	O
+up	O
+to	O
+50	O
+%	O
+the	O
+latency	O
+of	O
+access	O
+to	O
+shared	O
+objects	O
+compared	O
+to	O
+accessing	O
+the	O
+remote	O
+servers	O
+directly	O
+.	O
+
+Addressing	O
+Strategic	B-KEY
+Behavior	I-KEY
+in	O
+a	O
+Deployed	O
+Microeconomic	O
+Resource	B-KEY
+Allocator	I-KEY
+ABSTRACT	O
+While	O
+market-based	O
+systems	O
+have	O
+long	O
+been	O
+proposed	O
+as	O
+solutions	O
+for	O
+distributed	O
+resource	B-KEY
+allocation	I-KEY
+,	O
+few	O
+have	O
+been	O
+deployed	O
+for	O
+production	O
+use	O
+in	O
+real	O
+computer	O
+systems	O
+.	O
+Towards	O
+this	O
+end	O
+,	O
+we	O
+present	O
+our	O
+initial	O
+experience	O
+using	O
+Mirage	O
+,	O
+a	O
+microeconomic	O
+resource	B-KEY
+allocation	I-KEY
+system	O
+based	O
+on	O
+a	O
+repeated	O
+combinatorial	O
+auction	O
+.	O
+Mirage	O
+allocates	O
+time	O
+on	O
+a	O
+heavily-used	O
+148-node	O
+wireless	O
+sensor	O
+network	O
+testbed	O
+.	O
+In	O
+particular	O
+,	O
+we	O
+focus	O
+on	O
+observed	O
+strategic	O
+user	O
+behavior	O
+over	O
+a	O
+four-month	O
+period	O
+in	O
+which	O
+312,148	O
+node	O
+hours	O
+were	O
+allocated	O
+across	O
+11	O
+research	O
+projects	O
+.	O
+Based	O
+on	O
+these	O
+results	O
+,	O
+we	O
+present	O
+a	O
+set	O
+of	O
+key	O
+challenges	O
+for	O
+market-based	O
+resource	B-KEY
+allocation	I-KEY
+systems	O
+based	O
+on	O
+repeated	O
+combinatorial	O
+auctions	O
+.	O
+Finally	O
+,	O
+we	O
+propose	O
+refinements	O
+to	O
+the	O
+system	O
+'s	O
+current	O
+auction	O
+scheme	O
+to	O
+mitigate	O
+the	O
+strategies	O
+observed	O
+to	O
+date	O
+and	O
+also	O
+comment	O
+on	O
+some	O
+initial	O
+steps	O
+toward	O
+building	O
+an	O
+approximately	O
+strategyproof	O
+repeated	O
+combinatorial	B-KEY
+auction	I-KEY
+.	O
+
+Betting	B-KEY
+Boolean-Style	O
+:	O
+A	O
+Framework	O
+for	O
+Trading	O
+in	O
+Securities	O
+Based	O
+on	O
+Logical	O
+Formulas	O
+ABSTRACT	O
+We	O
+develop	O
+a	O
+framework	O
+for	O
+trading	O
+in	O
+compound	B-KEY
+securities	I-KEY
+:	O
+financial	O
+instruments	O
+that	O
+pay	O
+off	O
+contingent	O
+on	O
+the	O
+outcomes	O
+of	O
+arbitrary	O
+statements	O
+in	O
+propositional	O
+logic	O
+.	O
+Buying	O
+or	O
+selling	O
+securities	O
+--	O
+which	O
+can	O
+be	O
+thought	O
+of	O
+as	O
+betting	B-KEY
+on	O
+or	O
+against	O
+a	O
+particular	O
+future	O
+outcome	O
+--	O
+allows	O
+agents	O
+both	O
+to	O
+hedge	B-KEY
+risk	O
+and	O
+to	O
+profit	O
+-LRB-	O
+in	O
+expectation	O
+-RRB-	O
+on	O
+subjective	O
+predictions	O
+.	O
+A	O
+compound	B-KEY
+securities	I-KEY
+market	O
+allows	O
+agents	O
+to	O
+place	O
+bets	O
+on	O
+arbitrary	O
+boolean	O
+combinations	O
+of	O
+events	O
+,	O
+enabling	O
+them	O
+to	O
+more	O
+closely	O
+achieve	O
+their	O
+optimal	O
+risk	O
+exposure	O
+,	O
+and	O
+enabling	O
+the	O
+market	O
+as	O
+a	O
+whole	O
+to	O
+more	O
+closely	O
+achieve	O
+the	O
+social	O
+optimum	O
+.	O
+The	O
+tradeoff	O
+for	O
+allowing	O
+such	O
+expressivity	O
+is	O
+in	O
+the	O
+complexity	O
+of	O
+the	O
+agents	O
+'	O
+and	O
+auctioneer	O
+'s	O
+optimization	O
+problems	O
+.	O
+We	O
+develop	O
+and	O
+motivate	O
+the	O
+concept	O
+of	O
+a	O
+compound	B-KEY
+securities	I-KEY
+market	O
+,	O
+presenting	O
+the	O
+framework	O
+through	O
+a	O
+series	O
+of	O
+formal	O
+definitions	O
+and	O
+examples	O
+.	O
+We	O
+then	O
+analyze	O
+in	O
+detail	O
+the	O
+auctioneer	O
+'s	O
+matching	O
+problem	O
+.	O
+We	O
+show	O
+that	O
+,	O
+with	O
+n	O
+events	O
+,	O
+the	O
+matching	O
+problem	O
+is	O
+co-NP-complete	O
+in	O
+the	O
+divisible	O
+case	O
+and	O
+Σp2-complete	O
+in	O
+the	O
+indivisible	O
+case	O
+.	O
+We	O
+show	O
+that	O
+the	O
+latter	O
+hardness	O
+result	O
+holds	O
+even	O
+under	O
+severe	O
+language	O
+restrictions	O
+on	O
+bids	O
+.	O
+With	O
+log	O
+n	O
+events	O
+,	O
+the	O
+problem	O
+is	O
+polynomial	O
+in	O
+the	O
+divisible	O
+case	O
+and	O
+NP-complete	O
+in	O
+the	O
+indivisible	O
+case	O
+.	O
+We	O
+briefly	O
+discuss	O
+matching	O
+algorithms	O
+and	O
+tractable	O
+special	O
+cases	O
+.	O
+
+Robust	O
+Test	B-KEY
+Collections	I-KEY
+for	O
+Retrieval	O
+Evaluation	B-KEY
+ABSTRACT	O
+Low-cost	O
+methods	O
+for	O
+acquiring	O
+relevance	O
+judgments	O
+can	O
+be	O
+a	O
+boon	O
+to	O
+researchers	O
+who	O
+need	O
+to	O
+evaluate	B-KEY
+new	O
+retrieval	O
+tasks	O
+or	O
+topics	O
+but	O
+do	O
+not	O
+have	O
+the	O
+resources	O
+to	O
+make	O
+thousands	O
+of	O
+judgments	O
+.	O
+While	O
+these	O
+judgments	O
+are	O
+very	O
+useful	O
+for	O
+a	O
+one-time	O
+evaluation	B-KEY
+,	O
+it	O
+is	O
+not	O
+clear	O
+that	O
+they	O
+can	O
+be	O
+trusted	O
+when	O
+re-used	O
+to	O
+evaluate	B-KEY
+new	O
+systems	O
+.	O
+In	O
+this	O
+work	O
+,	O
+we	O
+formally	O
+define	O
+what	O
+it	O
+means	O
+for	O
+judgments	O
+to	O
+be	O
+reusable	B-KEY
+:	O
+the	O
+confidence	O
+in	O
+an	O
+evaluation	B-KEY
+of	O
+new	O
+systems	O
+can	O
+be	O
+accurately	O
+assessed	O
+from	O
+an	O
+existing	O
+set	O
+of	O
+relevance	O
+judgments	O
+.	O
+We	O
+then	O
+present	O
+a	O
+method	O
+for	O
+augmenting	O
+a	O
+set	O
+of	O
+relevance	O
+judgments	O
+with	O
+relevance	O
+estimates	O
+that	O
+require	O
+no	O
+additional	O
+assessor	O
+effort	O
+.	O
+Using	O
+this	O
+method	O
+practically	O
+guarantees	O
+reusability	B-KEY
+:	O
+with	O
+as	O
+few	O
+as	O
+five	O
+judgments	O
+per	O
+topic	O
+taken	O
+from	O
+only	O
+two	O
+systems	O
+,	O
+we	O
+can	O
+reliably	O
+evaluate	B-KEY
+a	O
+larger	O
+set	O
+of	O
+ten	O
+systems	O
+.	O
+Even	O
+the	O
+smallest	O
+sets	O
+of	O
+judgments	O
+can	O
+be	O
+useful	O
+for	O
+evaluation	B-KEY
+of	O
+new	O
+systems	O
+.	O
+
+Investigating	O
+the	O
+Querying	B-KEY
+and	O
+Browsing	O
+Behavior	O
+of	O
+Advanced	O
+Search	B-KEY
+Engine	I-KEY
+Users	O
+ABSTRACT	O
+One	O
+way	O
+to	O
+help	O
+all	O
+users	O
+of	O
+commercial	O
+Web	O
+search	B-KEY
+engines	I-KEY
+be	O
+more	O
+successful	O
+in	O
+their	O
+searches	O
+is	O
+to	O
+better	O
+understand	O
+what	O
+those	O
+users	O
+with	O
+greater	O
+search	O
+expertise	O
+are	O
+doing	O
+,	O
+and	O
+use	O
+this	O
+knowledge	O
+to	O
+benefit	O
+everyone	O
+.	O
+In	O
+this	O
+paper	O
+we	O
+study	O
+the	O
+interaction	O
+logs	O
+of	O
+advanced	O
+search	B-KEY
+engine	I-KEY
+users	O
+-LRB-	O
+and	O
+those	O
+not	O
+so	O
+advanced	O
+-RRB-	O
+to	O
+better	O
+understand	O
+how	O
+these	O
+user	O
+groups	O
+search	O
+.	O
+The	O
+results	O
+show	O
+that	O
+there	O
+are	O
+marked	O
+differences	O
+in	O
+the	O
+queries	B-KEY
+,	O
+result	O
+clicks	O
+,	O
+post-query	O
+browsing	O
+,	O
+and	O
+search	O
+success	O
+of	O
+users	O
+we	O
+classify	O
+as	O
+advanced	O
+-LRB-	O
+based	O
+on	O
+their	O
+use	O
+of	O
+query	O
+operators	O
+-RRB-	O
+,	O
+relative	O
+to	O
+those	O
+classified	O
+as	O
+non-advanced	O
+.	O
+Our	O
+findings	O
+have	O
+implications	O
+for	O
+how	O
+advanced	O
+users	O
+should	O
+be	O
+supported	O
+during	O
+their	O
+searches	O
+,	O
+and	O
+how	O
+their	O
+interactions	O
+could	O
+be	O
+used	O
+to	O
+help	O
+searchers	O
+of	O
+all	O
+experience	O
+levels	O
+find	O
+more	O
+relevant	B-KEY
+information	O
+and	O
+learn	O
+improved	O
+searching	O
+strategies	O
+.	O
+
+Dynamic	B-KEY
+Semantics	I-KEY
+for	O
+Agent	B-KEY
+Communication	I-KEY
+Languages	I-KEY
+ABSTRACT	O
+This	O
+paper	O
+proposes	O
+dynamic	B-KEY
+semantics	I-KEY
+for	O
+agent	B-KEY
+communication	I-KEY
+languages	I-KEY
+-LRB-	O
+ACLs	O
+-RRB-	O
+as	O
+a	O
+method	O
+for	O
+tackling	O
+some	O
+of	O
+the	O
+fundamental	O
+problems	O
+associated	O
+with	O
+agent	O
+communication	O
+in	O
+open	O
+multiagent	O
+systems	O
+.	O
+Based	O
+on	O
+the	O
+idea	O
+of	O
+providing	O
+alternative	O
+semantic	O
+``	O
+variants	O
+''	O
+for	O
+speech	O
+acts	O
+and	O
+transition	O
+rules	O
+between	O
+them	O
+that	O
+are	O
+contingent	O
+on	O
+previous	O
+agent	O
+behaviour	O
+,	O
+our	O
+framework	O
+provides	O
+an	O
+improved	O
+notion	O
+of	O
+grounding	O
+semantics	O
+in	O
+ongoing	O
+interaction	O
+,	O
+a	O
+simple	O
+mechanism	O
+for	O
+distinguishing	O
+between	O
+compliant	O
+and	O
+expected	O
+behaviour	O
+,	O
+and	O
+a	O
+way	O
+to	O
+specify	O
+sanction	O
+and	O
+reward	O
+mechanisms	O
+as	O
+part	O
+of	O
+the	O
+ACL	O
+itself	O
+.	O
+We	O
+extend	O
+a	O
+common	O
+framework	O
+for	O
+commitment-based	O
+ACL	O
+semantics	O
+to	O
+obtain	O
+these	O
+properties	O
+,	O
+discuss	O
+desiderata	O
+for	O
+the	O
+design	O
+of	O
+concrete	O
+dynamic	B-KEY
+semantics	I-KEY
+together	O
+with	O
+examples	O
+,	O
+and	O
+analyse	O
+their	O
+properties	O
+.	O
+
+Runtime	O
+Metrics	B-KEY
+Collection	I-KEY
+for	O
+Middleware	O
+Supported	O
+Adaptation	B-KEY
+of	O
+Mobile	O
+Applications	O
+ABSTRACT	O
+This	O
+paper	O
+proposes	O
+,	O
+implements	O
+,	O
+and	O
+evaluates	O
+in	O
+terms	O
+of	O
+worst	O
+case	O
+performance	O
+,	O
+an	O
+online	O
+metrics	B-KEY
+collection	I-KEY
+strategy	O
+to	O
+facilitate	O
+application	O
+adaptation	B-KEY
+via	O
+object	O
+mobility	O
+using	O
+a	O
+mobile	B-KEY
+object	I-KEY
+framework	O
+and	O
+supporting	O
+middleware	O
+.	O
+The	O
+solution	O
+is	O
+based	O
+upon	O
+an	O
+abstract	O
+representation	O
+of	O
+the	O
+mobile	B-KEY
+object	I-KEY
+system	O
+,	O
+which	O
+holds	O
+containers	O
+aggregating	O
+metrics	O
+for	O
+each	O
+specific	O
+component	O
+including	O
+host	O
+managers	O
+,	O
+runtimes	O
+and	O
+mobile	B-KEY
+objects	I-KEY
+.	O
+A	O
+key	O
+feature	O
+of	O
+the	O
+solution	O
+is	O
+the	O
+specification	O
+of	O
+multiple	O
+configurable	O
+criteria	O
+to	O
+control	O
+the	O
+measurement	B-KEY
+and	O
+propagation	O
+of	O
+metrics	O
+through	O
+the	O
+system	O
+.	O
+The	O
+MobJeX	B-KEY
+platform	O
+was	O
+used	O
+as	O
+the	O
+basis	O
+for	O
+implementation	O
+and	O
+testing	O
+with	O
+a	O
+number	O
+of	O
+laboratory	O
+tests	O
+conducted	O
+to	O
+measure	B-KEY
+scalability	O
+,	O
+efficiency	O
+and	O
+the	O
+application	O
+of	O
+simple	O
+measurement	B-KEY
+and	O
+propagation	O
+criteria	O
+to	O
+reduce	O
+collection	O
+overhead	O
+.	O
+
+Understanding	O
+User	O
+Behavior	O
+in	O
+Online	O
+Feedback	O
+Reporting	O
+ABSTRACT	O
+Online	B-KEY
+reviews	I-KEY
+have	O
+become	O
+increasingly	O
+popular	O
+as	O
+a	O
+way	O
+to	O
+judge	O
+the	O
+quality	O
+of	O
+various	O
+products	O
+and	O
+services	O
+.	O
+Previous	O
+work	O
+has	O
+demonstrated	O
+that	O
+contradictory	O
+reporting	O
+and	O
+underlying	O
+user	O
+biases	O
+make	O
+judging	O
+the	O
+true	O
+worth	O
+of	O
+a	O
+service	O
+difficult	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+investigate	O
+underlying	O
+factors	O
+that	O
+influence	O
+user	O
+behavior	O
+when	O
+reporting	O
+feedback	O
+.	O
+We	O
+look	O
+at	O
+two	O
+sources	O
+of	O
+information	O
+besides	O
+numerical	O
+ratings	B-KEY
+:	O
+linguistic	O
+evidence	O
+from	O
+the	O
+textual	O
+comment	O
+accompanying	O
+a	O
+review	O
+,	O
+and	O
+patterns	O
+in	O
+the	O
+time	O
+sequence	O
+of	O
+reports	O
+.	O
+We	O
+first	O
+show	O
+that	O
+groups	O
+of	O
+users	O
+who	O
+amply	O
+discuss	O
+a	O
+certain	O
+feature	O
+are	O
+more	O
+likely	O
+to	O
+agree	O
+on	O
+a	O
+common	O
+rating	B-KEY
+for	O
+that	O
+feature	O
+.	O
+Second	O
+,	O
+we	O
+show	O
+that	O
+a	O
+user	O
+'s	O
+rating	B-KEY
+partly	O
+reflects	O
+the	O
+difference	O
+between	O
+true	O
+quality	O
+and	O
+prior	O
+expectation	O
+of	O
+quality	O
+as	O
+inferred	O
+from	O
+previous	O
+reviews	O
+.	O
+Both	O
+give	O
+us	O
+a	O
+less	O
+noisy	O
+way	O
+to	O
+produce	O
+rating	B-KEY
+estimates	O
+and	O
+reveal	O
+the	O
+reasons	O
+behind	O
+user	O
+bias	O
+.	O
+Our	O
+hypotheses	O
+were	O
+validated	O
+by	O
+statistical	O
+evidence	O
+from	O
+hotel	O
+reviews	O
+on	O
+the	O
+TripAdvisor	O
+website	O
+.	O
+
+Temporal	O
+Linear	B-KEY
+Logic	I-KEY
+as	O
+a	O
+Basis	O
+for	O
+Flexible	O
+Agent	O
+Interactions	O
+ABSTRACT	O
+Interactions	O
+between	O
+agents	O
+in	O
+an	O
+open	O
+system	O
+such	O
+as	O
+the	O
+Internet	O
+require	O
+a	O
+significant	O
+degree	O
+of	O
+flexibility	O
+.	O
+A	O
+crucial	O
+aspect	O
+of	O
+the	O
+development	O
+of	O
+such	O
+methods	O
+is	O
+the	O
+notion	O
+of	O
+commitments	O
+,	O
+which	O
+provides	O
+a	O
+mechanism	O
+for	O
+coordinating	O
+interactive	B-KEY
+behaviors	I-KEY
+among	O
+agents	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+investigate	O
+an	O
+approach	O
+to	O
+model	O
+commitments	O
+with	O
+tight	O
+integration	O
+with	O
+protocol	O
+actions	O
+.	O
+This	O
+means	O
+that	O
+there	O
+is	O
+no	O
+need	O
+to	O
+have	O
+an	O
+explicit	O
+mapping	O
+from	O
+protocols	O
+actions	O
+to	O
+operations	O
+on	O
+commitments	O
+and	O
+an	O
+external	O
+mechanism	O
+to	O
+process	O
+and	O
+enforce	O
+commitments	O
+.	O
+We	O
+show	O
+how	O
+agents	O
+can	O
+reason	O
+about	O
+commitments	O
+and	O
+protocol	O
+actions	O
+to	O
+achieve	O
+the	O
+end	O
+results	O
+of	O
+protocols	O
+using	O
+a	O
+reasoning	O
+system	O
+based	O
+on	O
+temporal	O
+linear	B-KEY
+logic	I-KEY
+,	O
+which	O
+incorporates	O
+both	O
+temporal	O
+and	O
+resource-sensitive	O
+reasoning	O
+.	O
+We	O
+also	O
+discuss	O
+the	O
+application	O
+of	O
+this	O
+framework	O
+to	O
+scenarios	O
+such	O
+as	O
+online	O
+commerce	O
+.	O
+
+The	O
+Role	O
+of	O
+Compatibility	O
+in	O
+the	O
+Diffusion	O
+of	O
+Technologies	O
+Through	O
+Social	O
+Networks	O
+ABSTRACT	O
+In	O
+many	O
+settings	O
+,	O
+competing	O
+technologies	O
+--	O
+for	O
+example	O
+,	O
+operating	O
+systems	O
+,	O
+instant	O
+messenger	O
+systems	O
+,	O
+or	O
+document	O
+formats	O
+--	O
+can	O
+be	O
+seen	O
+adopting	O
+a	O
+limited	O
+amount	O
+of	O
+compatibility	O
+with	O
+one	O
+another	O
+;	O
+in	O
+other	O
+words	O
+,	O
+the	O
+difficulty	O
+in	O
+using	O
+multiple	O
+technologies	O
+is	O
+balanced	O
+somewhere	O
+between	O
+the	O
+two	O
+extremes	O
+of	O
+impossibility	O
+and	O
+effortless	O
+interoperability	B-KEY
+.	O
+There	O
+are	O
+a	O
+range	O
+of	O
+reasons	O
+why	O
+this	O
+phenomenon	O
+occurs	O
+,	O
+many	O
+of	O
+which	O
+--	O
+based	O
+on	O
+legal	O
+,	O
+social	O
+,	O
+or	O
+business	O
+considerations	O
+--	O
+seem	O
+to	O
+defy	O
+concise	O
+mathematical	O
+models	O
+.	O
+Despite	O
+this	O
+,	O
+we	O
+show	O
+that	O
+the	O
+advantages	O
+of	O
+limited	B-KEY
+compatibility	I-KEY
+can	O
+arise	O
+in	O
+a	O
+very	O
+simple	O
+model	O
+of	O
+diffusion	O
+in	O
+social	O
+networks	O
+,	O
+thus	O
+offering	O
+a	O
+basic	O
+explanation	O
+for	O
+this	O
+phenomenon	O
+in	O
+purely	O
+strategic	O
+terms	O
+.	O
+Our	O
+approach	O
+builds	O
+on	O
+work	O
+on	O
+the	O
+diffusion	B-KEY
+of	I-KEY
+innovations	I-KEY
+in	O
+the	O
+economics	O
+literature	O
+,	O
+which	O
+seeks	O
+to	O
+model	O
+how	O
+a	O
+new	O
+technology	O
+A	O
+might	O
+spread	O
+through	O
+a	O
+social	O
+network	O
+of	O
+individuals	O
+who	O
+are	O
+currently	O
+users	O
+of	O
+technology	O
+B	O
+.	O
+We	O
+consider	O
+several	O
+ways	O
+of	O
+capturing	O
+the	O
+compatibility	O
+of	O
+A	O
+and	O
+B	O
+,	O
+focusing	O
+primarily	O
+on	O
+a	O
+model	O
+in	O
+which	O
+users	O
+can	O
+choose	O
+to	O
+adopt	O
+A	O
+,	O
+adopt	O
+B	O
+,	O
+or	O
+--	O
+at	O
+an	O
+extra	O
+cost	O
+--	O
+adopt	O
+both	O
+A	O
+and	O
+B	O
+.	O
+We	O
+characterize	B-KEY
+how	O
+the	O
+ability	O
+of	O
+A	O
+to	O
+spread	O
+depends	O
+on	O
+both	O
+its	O
+quality	O
+relative	O
+to	O
+B	O
+,	O
+and	O
+also	O
+this	O
+additional	O
+cost	O
+of	O
+adopting	O
+both	O
+,	O
+and	O
+find	O
+some	O
+surprising	O
+non-monotonicity	O
+properties	O
+in	O
+the	O
+dependence	O
+on	O
+these	O
+parameters	O
+:	O
+in	O
+some	O
+cases	O
+,	O
+for	O
+one	O
+technology	O
+to	O
+survive	O
+the	O
+introduction	O
+of	O
+another	O
+,	O
+the	O
+cost	O
+of	O
+adopting	O
+both	O
+technologies	O
+must	O
+be	O
+balanced	O
+within	O
+a	O
+narrow	O
+,	O
+intermediate	O
+range	O
+.	O
+We	O
+also	O
+extend	O
+the	O
+framework	O
+to	O
+the	O
+case	O
+of	O
+multiple	O
+technologies	O
+,	O
+where	O
+we	O
+find	O
+that	O
+a	O
+simple	O
+This	O
+work	O
+has	O
+been	O
+supported	O
+in	O
+part	O
+by	O
+NSF	O
+grants	O
+CCF0325453	O
+,	O
+IIS-0329064	O
+,	O
+CNS-0403340	O
+,	O
+and	O
+BCS-0537606	O
+,	O
+a	O
+Google	O
+Research	O
+Grant	O
+,	O
+a	O
+Yahoo!	O
+Research	O
+Alliance	O
+Grant	O
+,	O
+the	O
+Institute	O
+for	O
+the	O
+Social	O
+Sciences	O
+at	O
+Cornell	O
+,	O
+and	O
+the	O
+John	O
+D.	O
+and	O
+Catherine	O
+T.	O
+MacArthur	O
+Foundation	O
+.	O
+model	O
+captures	O
+the	O
+phenomenon	O
+of	O
+two	O
+firms	O
+adopting	O
+a	O
+limited	O
+``	O
+strategic	O
+alliance	O
+''	O
+to	O
+defend	O
+against	O
+a	O
+new	O
+,	O
+third	O
+technology	O
+.	O
+
+Sensor	O
+Deployment	B-KEY
+Strategy	O
+for	O
+Target	B-KEY
+Detection	I-KEY
+ABSTRACT	O
+In	O
+order	O
+to	O
+monitor	O
+a	O
+region	O
+for	O
+traffic	O
+traversal	O
+,	O
+sensors	O
+can	O
+be	O
+deployed	B-KEY
+to	O
+perform	O
+collaborative	B-KEY
+target	I-KEY
+detection	I-KEY
+.	O
+Such	O
+a	O
+sensor	B-KEY
+network	I-KEY
+achieves	O
+a	O
+certain	O
+level	O
+of	O
+detection	O
+performance	O
+with	O
+an	O
+associated	O
+cost	O
+of	O
+deployment	B-KEY
+.	O
+This	O
+paper	O
+addresses	O
+this	O
+problem	O
+by	O
+proposing	O
+path	B-KEY
+exposure	I-KEY
+as	O
+a	O
+measure	O
+of	O
+the	O
+goodness	O
+of	O
+a	O
+deployment	O
+and	O
+presents	O
+an	O
+approach	O
+for	O
+sequential	O
+deployment	O
+in	O
+steps	O
+.	O
+It	O
+illustrates	O
+that	O
+the	O
+cost	O
+of	O
+deployment	B-KEY
+can	O
+be	O
+minimized	O
+to	O
+achieve	O
+the	O
+desired	O
+detection	O
+performance	O
+by	O
+appropriately	O
+choosing	O
+the	O
+number	B-KEY
+of	I-KEY
+sensors	I-KEY
+deployed	B-KEY
+in	O
+each	O
+step	O
+.	O
+
+Live	O
+Data	B-KEY
+Center	I-KEY
+Migration	I-KEY
+across	O
+WANs	B-KEY
+:	O
+A	O
+Robust	O
+Cooperative	O
+Context	O
+Aware	O
+Approach	O
+ABSTRACT	O
+A	O
+significant	O
+concern	O
+for	O
+Internet-based	O
+service	O
+providers	O
+is	O
+the	O
+continued	O
+operation	O
+and	O
+availability	O
+of	O
+services	O
+in	O
+the	O
+face	O
+of	O
+outages	O
+,	O
+whether	O
+planned	O
+or	O
+unplanned	O
+.	O
+In	O
+this	O
+paper	O
+we	O
+advocate	O
+a	O
+cooperative	O
+,	O
+context-aware	O
+approach	O
+to	O
+data	B-KEY
+center	I-KEY
+migration	I-KEY
+across	O
+WANs	B-KEY
+to	O
+deal	O
+with	O
+outages	O
+in	O
+a	O
+non-disruptive	O
+manner	O
+.	O
+We	O
+specifically	O
+seek	O
+to	O
+achieve	O
+high	O
+availability	O
+of	O
+data	O
+center	O
+services	O
+in	O
+the	O
+face	O
+of	O
+both	O
+planned	O
+and	O
+unanticipated	O
+outages	O
+of	O
+data	O
+center	O
+facilities	O
+.	O
+We	O
+make	O
+use	O
+of	O
+server	O
+virtualization	O
+technologies	O
+to	O
+enable	O
+the	O
+replication	O
+and	O
+migration	O
+of	O
+server	O
+functions	O
+.	O
+We	O
+propose	O
+new	O
+network	O
+functions	O
+to	O
+enable	O
+server	O
+migration	O
+and	O
+replication	O
+across	O
+wide	O
+area	O
+networks	O
+-LRB-	O
+e.g.	O
+,	O
+the	O
+Internet	O
+-RRB-	O
+,	O
+and	O
+finally	O
+show	O
+the	O
+utility	O
+of	O
+intelligent	O
+and	O
+dynamic	O
+storage	B-KEY
+replication	O
+technology	O
+to	O
+ensure	O
+applications	O
+have	O
+access	O
+to	O
+data	O
+in	O
+the	O
+face	O
+of	O
+outages	O
+with	O
+very	O
+tight	O
+recovery	O
+point	O
+objectives	O
+.	O
+
+Real-Time	O
+Agent	O
+Characterization	O
+and	O
+Prediction	B-KEY
+ABSTRACT	O
+Reasoning	O
+about	O
+agents	O
+that	O
+we	O
+observe	O
+in	O
+the	O
+world	O
+is	O
+challenging	O
+.	O
+Our	O
+available	O
+information	O
+is	O
+often	O
+limited	O
+to	O
+observations	O
+of	O
+the	O
+agent	O
+'s	O
+external	B-KEY
+behavior	I-KEY
+in	O
+the	O
+past	O
+and	O
+present	O
+.	O
+To	O
+understand	O
+these	O
+actions	O
+,	O
+we	O
+need	O
+to	O
+deduce	O
+the	O
+agent	O
+'s	O
+internal	B-KEY
+state	I-KEY
+,	O
+which	O
+includes	O
+not	O
+only	O
+rational	O
+elements	O
+-LRB-	O
+such	O
+as	O
+intentions	O
+and	O
+plans	O
+-RRB-	O
+,	O
+but	O
+also	O
+emotive	B-KEY
+ones	O
+-LRB-	O
+such	O
+as	O
+fear	O
+-RRB-	O
+.	O
+In	O
+addition	O
+,	O
+we	O
+often	O
+want	O
+to	O
+predict	B-KEY
+the	O
+agent	O
+'s	O
+future	O
+actions	O
+,	O
+which	O
+are	O
+constrained	O
+not	O
+only	O
+by	O
+these	O
+inward	O
+characteristics	O
+,	O
+but	O
+also	O
+by	O
+the	O
+dynamics	B-KEY
+of	O
+the	O
+agent	O
+'s	O
+interaction	O
+with	O
+its	O
+environment	O
+.	O
+BEE	O
+-LRB-	O
+Behavior	O
+Evolution	B-KEY
+and	O
+Extrapolation	O
+-RRB-	O
+uses	O
+a	O
+faster-than-real-time	O
+agentbased	O
+model	O
+of	O
+the	O
+environment	O
+to	O
+characterize	O
+agents	O
+'	O
+internal	O
+state	O
+by	O
+evolution	O
+against	O
+observed	O
+behavior	O
+,	O
+and	O
+then	O
+predict	O
+their	O
+future	O
+behavior	O
+,	O
+taking	O
+into	O
+account	O
+the	O
+dynamics	O
+of	O
+their	O
+interaction	O
+with	O
+the	O
+environment	O
+.	O
+
+A	O
+Support	O
+Vector	O
+Method	O
+for	O
+Optimizing	O
+Average	O
+Precision	O
+ABSTRACT	O
+Machine	B-KEY
+learning	I-KEY
+is	O
+commonly	O
+used	O
+to	O
+improve	O
+ranked	B-KEY
+retrieval	O
+systems	O
+.	O
+Due	O
+to	O
+computational	O
+difficulties	O
+,	O
+few	O
+learning	B-KEY
+techniques	I-KEY
+have	O
+been	O
+developed	O
+to	O
+directly	O
+optimize	O
+for	O
+mean	B-KEY
+average	I-KEY
+precision	I-KEY
+-LRB-	O
+MAP	O
+-RRB-	O
+,	O
+despite	O
+its	O
+widespread	O
+use	O
+in	O
+evaluating	O
+such	O
+systems	O
+.	O
+Existing	O
+approaches	O
+optimizing	O
+MAP	O
+either	O
+do	O
+not	O
+find	O
+a	O
+globally	O
+optimal	B-KEY
+solution	I-KEY
+,	O
+or	O
+are	O
+computationally	O
+expensive	O
+.	O
+In	O
+contrast	O
+,	O
+we	O
+present	O
+a	O
+general	O
+SVM	O
+learning	O
+algorithm	O
+that	O
+efficiently	O
+finds	O
+a	O
+globally	O
+optimal	B-KEY
+solution	I-KEY
+to	O
+a	O
+straightforward	O
+relaxation	B-KEY
+of	I-KEY
+MAP	I-KEY
+.	O
+We	O
+evaluate	O
+our	O
+approach	O
+using	O
+the	O
+TREC	O
+9	O
+and	O
+TREC	O
+10	O
+Web	O
+Track	O
+corpora	O
+-LRB-	O
+WT10g	O
+-RRB-	O
+,	O
+comparing	O
+against	O
+SVMs	O
+optimized	O
+for	O
+accuracy	O
+and	O
+ROCArea	O
+.	O
+In	O
+most	O
+cases	O
+we	O
+show	O
+our	O
+method	O
+to	O
+produce	O
+statistically	O
+significant	O
+improvements	O
+in	O
+MAP	O
+scores	O
+.	O
+
+Encryption-Enforced	O
+Access	O
+Control	O
+in	O
+Dynamic	O
+Multi-Domain	B-KEY
+Publish/Subscribe	O
+Networks	O
+ABSTRACT	O
+Publish/subscribe	O
+systems	O
+provide	O
+an	O
+efficient	O
+,	O
+event-based	O
+,	O
+wide-area	O
+distributed	O
+communications	O
+infrastructure	O
+.	O
+Large	O
+scale	O
+publish/subscribe	O
+systems	O
+are	O
+likely	O
+to	O
+employ	O
+components	O
+of	O
+the	O
+event	O
+transport	O
+network	O
+owned	O
+by	O
+cooperating	O
+,	O
+but	O
+independent	O
+organisations	O
+.	O
+As	O
+the	O
+number	O
+of	O
+participants	O
+in	O
+the	O
+network	O
+increases	O
+,	O
+security	O
+becomes	O
+an	O
+increasing	O
+concern	O
+.	O
+This	O
+paper	O
+extends	O
+previous	O
+work	O
+to	O
+present	O
+and	O
+evaluate	O
+a	O
+secure	O
+multi-domain	B-KEY
+publish/subscribe	O
+infrastructure	O
+that	O
+supports	O
+and	O
+enforces	O
+fine-grained	O
+access	O
+control	O
+over	O
+the	O
+individual	O
+attributes	O
+of	O
+event	O
+types	O
+.	O
+Key	O
+refresh	O
+allows	O
+us	O
+to	O
+ensure	O
+forward	O
+and	O
+backward	O
+security	O
+when	O
+event	O
+brokers	O
+join	O
+and	O
+leave	O
+the	O
+network	O
+.	O
+We	O
+demonstrate	O
+that	O
+the	O
+time	O
+and	O
+space	O
+overheads	O
+can	O
+be	O
+minimised	O
+by	O
+careful	O
+consideration	O
+of	O
+encryption	B-KEY
+techniques	O
+,	O
+and	O
+by	O
+the	O
+use	O
+of	O
+caching	O
+to	O
+decrease	O
+unnecessary	O
+decryptions	O
+.	O
+We	O
+show	O
+that	O
+our	O
+approach	O
+has	O
+a	O
+smaller	O
+overall	B-KEY
+communication	I-KEY
+overhead	I-KEY
+than	O
+existing	O
+approaches	O
+for	O
+achieving	O
+the	O
+same	O
+degree	O
+of	O
+control	O
+over	O
+security	O
+in	O
+publish/subscribe	O
+networks	O
+.	O
+
+A	O
+Framework	O
+for	O
+Architecting	O
+Peer-to-Peer	O
+Receiver-driven	O
+Overlays	O
+ABSTRACT	O
+This	O
+paper	O
+presents	O
+a	O
+simple	O
+and	O
+scalable	O
+framework	O
+for	O
+architecting	O
+peer-to-peer	O
+overlays	O
+called	O
+Peer-to-peer	O
+Receiverdriven	O
+Overlay	O
+-LRB-	O
+or	O
+PRO	B-KEY
+-RRB-	O
+.	O
+PRO	B-KEY
+is	O
+designed	B-KEY
+for	O
+non-interactive	O
+streaming	O
+applications	O
+and	O
+its	O
+primary	O
+design	B-KEY
+goal	O
+is	O
+to	O
+maximize	O
+delivered	O
+bandwidth	O
+-LRB-	O
+and	O
+thus	O
+delivered	O
+quality	O
+-RRB-	O
+to	O
+peers	O
+with	O
+heterogeneous	O
+and	O
+asymmetric	O
+bandwidth	O
+.	O
+To	O
+achieve	O
+this	O
+goal	O
+,	O
+PRO	B-KEY
+adopts	O
+a	O
+receiver-driven	O
+approach	O
+where	O
+each	O
+receiver	O
+-LRB-	O
+or	O
+participating	O
+peer	O
+-RRB-	O
+-LRB-	O
+i	O
+-RRB-	O
+independently	O
+discovers	O
+other	O
+peers	O
+in	O
+the	O
+overlay	O
+through	O
+gossiping	O
+,	O
+and	O
+-LRB-	O
+ii	O
+-RRB-	O
+selfishly	O
+determines	O
+the	O
+best	O
+subset	O
+of	O
+parent	O
+peers	O
+through	O
+which	O
+to	O
+connect	O
+to	O
+the	O
+overlay	O
+to	O
+maximize	O
+its	O
+own	O
+delivered	O
+bandwidth	O
+.	O
+Participating	O
+peers	O
+form	O
+an	O
+unstructured	O
+overlay	O
+which	O
+is	O
+inherently	O
+robust	O
+to	O
+high	O
+churn	O
+rate	O
+.	O
+Furthermore	O
+,	O
+each	O
+receiver	O
+leverages	O
+congestion	B-KEY
+controlled	I-KEY
+bandwidth	O
+from	O
+its	O
+parents	O
+as	O
+implicit	O
+signal	O
+to	O
+detect	O
+and	O
+react	O
+to	O
+long-term	O
+changes	O
+in	O
+network	O
+or	O
+overlay	O
+condition	O
+without	O
+any	O
+explicit	O
+coordination	O
+with	O
+other	O
+participating	O
+peers	O
+.	O
+Independent	O
+parent	O
+selection	O
+by	O
+individual	O
+peers	O
+dynamically	O
+converge	O
+to	O
+an	O
+efficient	O
+overlay	O
+structure	O
+.	O
+
+A	O
+Study	O
+of	O
+Poisson	O
+Query	B-KEY
+Generation	I-KEY
+Model	O
+for	O
+Information	O
+Retrieval	O
+ABSTRACT	O
+Many	O
+variants	O
+of	O
+language	B-KEY
+models	I-KEY
+have	O
+been	O
+proposed	O
+for	O
+information	O
+retrieval	O
+.	O
+Most	O
+existing	O
+models	O
+are	O
+based	O
+on	O
+multinomial	B-KEY
+distribution	I-KEY
+and	O
+would	O
+score	O
+documents	O
+based	O
+on	O
+query	O
+likelihood	O
+computed	O
+based	O
+on	O
+a	O
+query	B-KEY
+generation	I-KEY
+probabilistic	O
+model	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+propose	O
+and	O
+study	O
+a	O
+new	O
+family	O
+of	O
+query	B-KEY
+generation	I-KEY
+models	O
+based	O
+on	O
+Poisson	B-KEY
+distribution	I-KEY
+.	O
+We	O
+show	O
+that	O
+while	O
+in	O
+their	O
+simplest	O
+forms	O
+,	O
+the	O
+new	O
+family	O
+of	O
+models	O
+and	O
+the	O
+existing	O
+multinomial	O
+models	O
+are	O
+equivalent	O
+,	O
+they	O
+behave	O
+differently	O
+for	O
+many	O
+smoothing	O
+methods	O
+.	O
+We	O
+show	O
+that	O
+the	O
+Poisson	O
+model	O
+has	O
+several	O
+advantages	O
+over	O
+the	O
+multinomial	O
+model	O
+,	O
+including	O
+naturally	O
+accommodating	O
+per-term	O
+smoothing	O
+and	O
+allowing	O
+for	O
+more	O
+accurate	O
+background	O
+modeling	O
+.	O
+We	O
+present	O
+several	O
+variants	O
+of	O
+the	O
+new	O
+model	O
+corresponding	O
+to	O
+different	O
+smoothing	O
+methods	O
+,	O
+and	O
+evaluate	O
+them	O
+on	O
+four	O
+representative	O
+TREC	O
+test	O
+collections	O
+.	O
+The	O
+results	O
+show	O
+that	O
+while	O
+their	O
+basic	O
+models	O
+perform	O
+comparably	O
+,	O
+the	O
+Poisson	O
+model	O
+can	O
+outperform	O
+multinomial	O
+model	O
+with	O
+per-term	O
+smoothing	O
+.	O
+The	O
+performance	O
+can	O
+be	O
+further	O
+improved	O
+with	O
+two-stage	O
+smoothing	O
+.	O
+
+Personalized	O
+Query	B-KEY
+Expansion	I-KEY
+for	O
+the	O
+Web	O
+ABSTRACT	O
+The	O
+inherent	O
+ambiguity	O
+of	O
+short	B-KEY
+keyword	I-KEY
+queries	I-KEY
+demands	O
+for	O
+enhanced	O
+methods	O
+for	O
+Web	B-KEY
+retrieval	I-KEY
+.	O
+In	O
+this	O
+paper	O
+we	O
+propose	O
+to	O
+improve	O
+such	O
+Web	B-KEY
+queries	I-KEY
+by	O
+expanding	O
+them	O
+with	O
+terms	O
+collected	O
+from	O
+each	O
+user	O
+'s	O
+Personal	B-KEY
+Information	I-KEY
+Repository	I-KEY
+,	O
+thus	O
+implicitly	O
+personalizing	O
+the	O
+search	B-KEY
+output	I-KEY
+.	O
+We	O
+introduce	O
+five	O
+broad	O
+techniques	O
+for	O
+generating	O
+the	O
+additional	B-KEY
+query	I-KEY
+keywords	I-KEY
+by	O
+analyzing	O
+user	O
+data	O
+at	O
+increasing	O
+granularity	B-KEY
+levels	I-KEY
+,	O
+ranging	O
+from	O
+term	B-KEY
+and	I-KEY
+compound	I-KEY
+level	I-KEY
+analysis	I-KEY
+up	O
+to	O
+global	B-KEY
+co-occurrence	I-KEY
+statistics	I-KEY
+,	O
+as	O
+well	O
+as	O
+to	O
+using	O
+external	O
+thesauri	O
+.	O
+Our	O
+extensive	B-KEY
+empirical	I-KEY
+analysis	I-KEY
+under	O
+four	O
+different	O
+scenarios	O
+shows	O
+some	O
+of	O
+these	O
+approaches	O
+to	O
+perform	O
+very	O
+well	O
+,	O
+especially	O
+on	O
+ambiguous	B-KEY
+queries	I-KEY
+,	O
+producing	O
+a	O
+very	O
+strong	O
+increase	O
+in	O
+the	O
+quality	B-KEY
+of	O
+the	O
+output	B-KEY
+rankings	I-KEY
+.	O
+Subsequently	O
+,	O
+we	O
+move	O
+this	O
+personalized	B-KEY
+search	I-KEY
+framework	I-KEY
+one	O
+step	O
+further	O
+and	O
+propose	O
+to	O
+make	O
+the	O
+expansion	B-KEY
+process	I-KEY
+adaptive	O
+to	O
+various	B-KEY
+features	I-KEY
+of	I-KEY
+each	I-KEY
+query	I-KEY
+.	O
+A	O
+separate	O
+set	O
+of	O
+experiments	O
+indicates	O
+the	O
+adaptive	B-KEY
+algorithms	I-KEY
+to	O
+bring	O
+an	O
+additional	O
+statistically	O
+significant	B-KEY
+improvement	I-KEY
+over	O
+the	O
+best	O
+static	B-KEY
+expansion	I-KEY
+approach	I-KEY
+.	O
+
+Efficient	O
+Bayesian	O
+Hierarchical	O
+User	O
+Modeling	B-KEY
+for	O
+Recommendation	B-KEY
+Systems	I-KEY
+ABSTRACT	O
+A	O
+content-based	O
+personalized	B-KEY
+recommendation	B-KEY
+system	I-KEY
+learns	O
+user	O
+specific	O
+profiles	O
+from	O
+user	O
+feedback	O
+so	O
+that	O
+it	O
+can	O
+deliver	O
+information	O
+tailored	O
+to	O
+each	O
+individual	O
+user	O
+'s	O
+interest	O
+.	O
+A	O
+system	O
+serving	O
+millions	O
+of	O
+users	O
+can	O
+learn	O
+a	O
+better	O
+user	O
+profile	O
+for	O
+a	O
+new	O
+user	O
+,	O
+or	O
+a	O
+user	O
+with	O
+little	O
+feedback	O
+,	O
+by	O
+borrowing	O
+information	O
+from	O
+other	O
+users	O
+through	O
+the	O
+use	O
+of	O
+a	O
+Bayesian	B-KEY
+hierarchical	I-KEY
+model	I-KEY
+.	O
+Learning	O
+the	O
+model	B-KEY
+parameters	B-KEY
+to	O
+optimize	O
+the	O
+joint	O
+data	O
+likelihood	O
+from	O
+millions	O
+of	O
+users	O
+is	O
+very	O
+computationally	O
+expensive	O
+.	O
+The	O
+commonly	O
+used	O
+EM	B-KEY
+algorithm	I-KEY
+converges	O
+very	O
+slowly	O
+due	O
+to	O
+the	O
+sparseness	O
+of	O
+the	O
+data	O
+in	O
+IR	B-KEY
+applications	O
+.	O
+This	O
+paper	O
+proposes	O
+a	O
+new	O
+fast	O
+learning	B-KEY
+technique	I-KEY
+to	O
+learn	O
+a	O
+large	O
+number	O
+of	O
+individual	O
+user	O
+profiles	O
+.	O
+The	O
+efficacy	O
+and	O
+efficiency	O
+of	O
+the	O
+proposed	O
+algorithm	O
+are	O
+justified	O
+by	O
+theory	O
+and	O
+demonstrated	O
+on	O
+actual	O
+user	O
+data	O
+from	O
+Netflix	O
+and	O
+MovieLens	O
+.	O
+
+Sharing	O
+Experiences	O
+to	O
+Learn	O
+User	O
+Characteristics	O
+in	O
+Dynamic	O
+Environments	O
+with	O
+Sparse	O
+Data	O
+ABSTRACT	O
+This	O
+paper	O
+investigates	O
+the	O
+problem	O
+of	O
+estimating	O
+the	O
+value	O
+of	O
+probabilistic	B-KEY
+parameters	I-KEY
+needed	O
+for	O
+decision	B-KEY
+making	I-KEY
+in	O
+environments	O
+in	O
+which	O
+an	O
+agent	B-KEY
+,	O
+operating	O
+within	O
+a	O
+multi-agent	O
+system	O
+,	O
+has	O
+no	O
+a	O
+priori	O
+information	O
+about	O
+the	O
+structure	O
+of	O
+the	O
+distribution	O
+of	O
+parameter	O
+values	O
+.	O
+The	O
+agent	B-KEY
+must	O
+be	O
+able	O
+to	O
+produce	O
+estimations	O
+even	O
+when	O
+it	O
+may	O
+have	O
+made	O
+only	O
+a	O
+small	O
+number	O
+of	O
+direct	O
+observations	O
+,	O
+and	O
+thus	O
+it	O
+must	O
+be	O
+able	O
+to	O
+operate	O
+with	O
+sparse	O
+data	O
+.	O
+The	O
+paper	O
+describes	O
+a	O
+mechanism	O
+that	O
+enables	O
+the	O
+agent	B-KEY
+to	O
+significantly	O
+improve	O
+its	O
+estimation	O
+by	O
+augmenting	O
+its	O
+direct	O
+observations	O
+with	O
+those	O
+obtained	O
+by	O
+other	O
+agents	B-KEY
+with	O
+which	O
+it	O
+is	O
+coordinating	O
+.	O
+To	O
+avoid	O
+undesirable	O
+bias	O
+in	O
+relatively	O
+heterogeneous	O
+environments	O
+while	O
+effectively	O
+using	O
+relevant	O
+data	O
+to	O
+improve	O
+its	O
+estimations	O
+,	O
+the	O
+mechanism	O
+weighs	O
+the	O
+contributions	O
+of	O
+other	O
+agents	B-KEY
+'	O
+observations	O
+based	O
+on	O
+a	O
+real-time	O
+estimation	O
+of	O
+the	O
+level	O
+of	O
+similarity	O
+between	O
+each	O
+of	O
+these	O
+agents	B-KEY
+and	O
+itself	O
+.	O
+The	O
+``	O
+coordination	O
+autonomy	O
+''	O
+module	O
+of	O
+a	O
+coordination-manager	O
+system	O
+provided	O
+an	O
+empirical	O
+setting	O
+for	O
+evaluation	O
+.	O
+Simulation-based	O
+evaluations	O
+demonstrated	O
+that	O
+the	O
+proposed	O
+mechanism	O
+outperforms	O
+estimations	O
+based	O
+exclusively	O
+on	O
+an	O
+agent	B-KEY
+'s	O
+own	O
+observations	O
+as	O
+well	O
+as	O
+estimations	O
+based	O
+on	O
+an	O
+unweighted	O
+aggregate	O
+of	O
+all	O
+other	O
+agents	B-KEY
+'	O
+observations	O
+.	O
+
+Researches	O
+on	O
+Scheme	O
+of	O
+Pairwise	O
+Key	O
+Establishment	O
+for	O
+Distributed	O
+Sensor	B-KEY
+Networks	I-KEY
+ABSTRACT	O
+Security	B-KEY
+schemes	O
+of	O
+pairwise	O
+key	O
+establishment	O
+,	O
+which	O
+enable	O
+sensors	O
+to	O
+communicate	O
+with	O
+each	O
+other	O
+securely	B-KEY
+,	O
+play	O
+a	O
+fundamental	O
+role	O
+in	O
+research	O
+on	O
+security	B-KEY
+issue	O
+in	O
+wireless	O
+sensor	B-KEY
+networks	I-KEY
+.	O
+A	O
+new	O
+kind	O
+of	O
+cluster	O
+deployed	O
+sensor	B-KEY
+networks	I-KEY
+distribution	O
+model	O
+is	O
+presented	O
+,	O
+and	O
+based	O
+on	O
+which	O
+,	O
+an	O
+innovative	O
+Hierarchical	B-KEY
+Hypercube	I-KEY
+model	I-KEY
+-	O
+H	O
+-LRB-	O
+k	O
+,	O
+u	O
+,	O
+m	O
+,	O
+v	O
+,	O
+n	O
+-RRB-	O
+and	O
+the	O
+mapping	O
+relationship	O
+between	O
+cluster	O
+deployed	O
+sensor	B-KEY
+networks	I-KEY
+and	O
+the	O
+H	O
+-LRB-	O
+k	O
+,	O
+u	O
+,	O
+m	O
+,	O
+v	O
+,	O
+n	O
+-RRB-	O
+are	O
+proposed	O
+.	O
+By	O
+utilizing	O
+nice	O
+properties	O
+of	O
+H	O
+-LRB-	O
+k	O
+,	O
+u	O
+,	O
+m	O
+,	O
+v	O
+,	O
+n	O
+-RRB-	O
+model	O
+,	O
+a	O
+new	O
+general	O
+framework	O
+for	O
+pairwise	O
+key	O
+predistribution	O
+and	O
+a	O
+new	O
+pairwise	O
+key	O
+establishment	O
+algorithm	O
+are	O
+designed	O
+,	O
+which	O
+combines	O
+the	O
+idea	O
+of	O
+KDC	O
+-LRB-	O
+Key	O
+Distribution	O
+Center	O
+-RRB-	O
+and	O
+polynomial	O
+pool	O
+schemes	O
+.	O
+Furthermore	O
+,	O
+the	O
+working	O
+performance	O
+of	O
+the	O
+newly	O
+proposed	O
+pairwise	O
+key	O
+establishment	O
+algorithm	O
+is	O
+seriously	O
+inspected	O
+.	O
+Theoretic	O
+analysis	O
+and	O
+experimental	O
+figures	O
+show	O
+that	O
+the	O
+new	O
+algorithm	O
+has	O
+better	O
+performance	O
+and	O
+provides	O
+higher	O
+possibilities	O
+for	O
+sensor	O
+to	O
+establish	O
+pairwise	O
+key	O
+,	O
+compared	O
+with	O
+previous	O
+related	O
+works	O
+.	O
+
+Interactions	O
+between	O
+Market	B-KEY
+Barriers	I-KEY
+and	O
+Communication	O
+Networks	O
+in	O
+Marketing	B-KEY
+Systems	I-KEY
+ABSTRACT	O
+We	O
+investigate	O
+a	O
+framework	O
+where	O
+agents	O
+search	O
+for	O
+satisfying	O
+products	O
+by	O
+using	O
+referrals	O
+from	O
+other	O
+agents	O
+.	O
+Our	O
+model	O
+of	O
+a	O
+mechanism	O
+for	O
+transmitting	O
+word-of-mouth	O
+and	O
+the	O
+resulting	O
+behavioural	O
+effects	O
+is	O
+based	O
+on	O
+integrating	O
+a	O
+module	O
+governing	O
+the	O
+local	O
+behaviour	O
+of	O
+agents	O
+with	O
+a	O
+module	O
+governing	O
+the	O
+structure	O
+and	O
+function	O
+of	O
+the	O
+underlying	O
+network	O
+of	O
+agents	O
+.	O
+Local	O
+behaviour	O
+incorporates	O
+a	O
+satisficing	O
+model	O
+of	O
+choice	O
+,	O
+a	O
+set	O
+of	O
+rules	O
+governing	O
+the	O
+interactions	O
+between	O
+agents	O
+,	O
+including	O
+learning	O
+about	O
+the	O
+trustworthiness	O
+of	O
+other	O
+agents	O
+over	O
+time	O
+,	O
+and	O
+external	O
+constraints	O
+on	O
+behaviour	O
+that	O
+may	O
+be	O
+imposed	O
+by	O
+market	B-KEY
+barriers	I-KEY
+or	O
+switching	B-KEY
+costs	I-KEY
+.	O
+Local	O
+behaviour	O
+takes	O
+place	O
+on	O
+a	O
+network	O
+substrate	O
+across	O
+which	O
+agents	O
+exchange	O
+positive	O
+and	O
+negative	O
+information	O
+about	O
+products	O
+.	O
+We	O
+use	O
+various	O
+degree	O
+distributions	O
+dictating	O
+the	O
+extent	O
+of	O
+connectivity	O
+,	O
+and	O
+incorporate	O
+both	O
+small-world	O
+effects	O
+and	O
+the	O
+notion	O
+of	O
+preferential	O
+attachment	O
+in	O
+our	O
+network	O
+models	O
+.	O
+We	O
+compare	O
+the	O
+effectiveness	O
+of	O
+referral	B-KEY
+systems	I-KEY
+over	O
+various	O
+network	O
+structures	O
+for	O
+easy	O
+and	O
+hard	O
+choice	O
+tasks	O
+,	O
+and	O
+evaluate	O
+how	O
+this	O
+effectiveness	O
+changes	O
+with	O
+the	O
+imposition	O
+of	O
+market	B-KEY
+barriers	I-KEY
+.	O
+
+A	O
+Reinforcement	B-KEY
+Learning	I-KEY
+based	O
+Distributed	B-KEY
+Search	I-KEY
+Algorithm	I-KEY
+For	O
+Hierarchical	O
+Peer-to-Peer	O
+Information	O
+Retrieval	O
+Systems	O
+ABSTRACT	O
+The	O
+dominant	O
+existing	O
+routing	O
+strategies	O
+employed	O
+in	O
+peerto-peer	O
+-LRB-	O
+P2P	O
+-RRB-	O
+based	O
+information	O
+retrieval	O
+-LRB-	O
+IR	O
+-RRB-	O
+systems	O
+are	O
+similarity-based	O
+approaches	O
+.	O
+In	O
+these	O
+approaches	O
+,	O
+agents	O
+depend	O
+on	O
+the	O
+content	O
+similarity	O
+between	O
+incoming	O
+queries	B-KEY
+and	O
+their	O
+direct	O
+neighboring	O
+agents	O
+to	O
+direct	O
+the	O
+distributed	O
+search	O
+sessions	O
+.	O
+However	O
+,	O
+such	O
+a	O
+heuristic	O
+is	O
+myopic	O
+in	O
+that	O
+the	O
+neighboring	O
+agents	O
+may	O
+not	O
+be	O
+connected	O
+to	O
+more	O
+relevant	O
+agents	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+an	O
+online	O
+reinforcement-learning	O
+based	O
+approach	O
+is	O
+developed	O
+to	O
+take	O
+advantage	O
+of	O
+the	O
+dynamic	O
+run-time	O
+characteristics	O
+of	O
+P2P	O
+IR	O
+systems	O
+as	O
+represented	O
+by	O
+information	O
+about	O
+past	O
+search	O
+sessions	O
+.	O
+Specifically	O
+,	O
+agents	O
+maintain	O
+estimates	O
+on	O
+the	O
+downstream	O
+agents	O
+'	O
+abilities	O
+to	O
+provide	O
+relevant	O
+documents	O
+for	O
+incoming	O
+queries	B-KEY
+.	O
+These	O
+estimates	O
+are	O
+updated	O
+gradually	O
+by	O
+learning	O
+from	O
+the	O
+feedback	O
+information	O
+returned	O
+from	O
+previous	O
+search	O
+sessions	O
+.	O
+Based	O
+on	O
+this	O
+information	O
+,	O
+the	O
+agents	O
+derive	O
+corresponding	O
+routing	B-KEY
+policies	I-KEY
+.	O
+Thereafter	O
+,	O
+these	O
+agents	O
+route	O
+the	O
+queries	B-KEY
+based	O
+on	O
+the	O
+learned	O
+policies	O
+and	O
+update	O
+the	O
+estimates	O
+based	O
+on	O
+the	O
+new	O
+routing	B-KEY
+policies	I-KEY
+.	O
+Experimental	O
+results	O
+demonstrate	O
+that	O
+the	O
+learning	B-KEY
+algorithm	I-KEY
+improves	O
+considerably	O
+the	O
+routing	O
+performance	O
+on	O
+two	O
+test	O
+collection	O
+sets	O
+that	O
+have	O
+been	O
+used	O
+in	O
+a	O
+variety	O
+of	O
+distributed	O
+IR	O
+studies	O
+.	O
+
+Computing	O
+the	O
+Optimal	B-KEY
+Strategy	I-KEY
+to	O
+Commit	B-KEY
+to	O
+∗	O
+ABSTRACT	O
+In	O
+multiagent	B-KEY
+systems	I-KEY
+,	O
+strategic	O
+settings	O
+are	O
+often	O
+analyzed	O
+under	O
+the	O
+assumption	O
+that	O
+the	O
+players	O
+choose	O
+their	O
+strategies	O
+simultaneously	O
+.	O
+However	O
+,	O
+this	O
+model	O
+is	O
+not	O
+always	O
+realistic	O
+.	O
+In	O
+many	O
+settings	O
+,	O
+one	O
+player	O
+is	O
+able	O
+to	O
+commit	B-KEY
+to	O
+a	O
+strategy	O
+before	O
+the	O
+other	O
+player	O
+makes	O
+a	O
+decision	O
+.	O
+Such	O
+models	O
+are	O
+synonymously	O
+referred	O
+to	O
+as	O
+leadership	B-KEY
+,	O
+commitment	B-KEY
+,	O
+or	O
+Stackelberg	B-KEY
+models	O
+,	O
+and	O
+optimal	O
+play	O
+in	O
+such	O
+models	O
+is	O
+often	O
+significantly	O
+different	O
+from	O
+optimal	O
+play	O
+in	O
+the	O
+model	O
+where	O
+strategies	O
+are	O
+selected	O
+simultaneously	O
+.	O
+The	O
+recent	O
+surge	O
+in	O
+interest	O
+in	O
+computing	O
+game-theoretic	O
+solutions	O
+has	O
+so	O
+far	O
+ignored	O
+leadership	B-KEY
+models	O
+-LRB-	O
+with	O
+the	O
+exception	O
+of	O
+the	O
+interest	O
+in	O
+mechanism	O
+design	O
+,	O
+where	O
+the	O
+designer	O
+is	O
+implicitly	O
+in	O
+a	O
+leadership	O
+position	O
+-RRB-	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+study	O
+how	O
+to	O
+compute	O
+optimal	B-KEY
+strategies	I-KEY
+to	O
+commit	B-KEY
+to	O
+under	O
+both	O
+commitment	B-KEY
+to	O
+pure	B-KEY
+strategies	I-KEY
+and	O
+commitment	B-KEY
+to	O
+mixed	B-KEY
+strategies	I-KEY
+,	O
+in	O
+both	O
+normal-form	O
+and	O
+Bayesian	B-KEY
+games	I-KEY
+.	O
+We	O
+give	O
+both	O
+positive	O
+results	O
+-LRB-	O
+efficient	O
+algorithms	O
+-RRB-	O
+and	O
+negative	O
+results	O
+-LRB-	O
+NP-hardness	B-KEY
+results	O
+-RRB-	O
+.	O
+
+Edge	B-KEY
+Indexing	I-KEY
+in	O
+a	O
+Grid	O
+for	O
+Highly	O
+Dynamic	B-KEY
+Virtual	I-KEY
+Environments	I-KEY
+∗	O
+ABSTRACT	O
+Newly	O
+emerging	O
+game	O
+--	O
+based	O
+application	O
+systems	O
+such	O
+as	O
+Second	O
+Life1	O
+provide	O
+3D	O
+virtual	O
+environments	O
+where	O
+multiple	O
+users	O
+interact	O
+with	O
+each	O
+other	O
+in	O
+real	O
+--	O
+time	O
+.	O
+They	O
+are	O
+filled	O
+with	O
+autonomous	O
+,	O
+mutable	B-KEY
+virtual	I-KEY
+content	I-KEY
+which	O
+is	O
+continuously	O
+augmented	O
+by	O
+the	O
+users	O
+.	O
+To	O
+make	O
+the	O
+systems	O
+highly	O
+scalable	O
+and	O
+dynamically	O
+extensible	O
+,	O
+they	O
+are	O
+usually	O
+built	O
+on	O
+a	O
+client	O
+--	O
+server	O
+based	O
+grid	O
+subspace	O
+division	O
+where	O
+the	O
+virtual	O
+worlds	O
+are	O
+partitioned	O
+into	O
+manageable	O
+sub	O
+--	O
+worlds	O
+.	O
+In	O
+each	O
+sub	O
+--	O
+world	O
+,	O
+the	O
+user	O
+continuously	O
+receives	O
+relevant	O
+geometry	O
+updates	O
+of	O
+moving	O
+objects	O
+from	O
+remotely	O
+connected	O
+servers	O
+and	O
+renders	O
+them	O
+according	O
+to	O
+her	O
+viewpoint	O
+,	O
+rather	O
+than	O
+retrieving	O
+them	O
+from	O
+a	O
+local	O
+storage	O
+medium	O
+.	O
+In	O
+such	O
+systems	O
+,	O
+the	O
+determination	O
+of	O
+the	O
+set	O
+of	O
+objects	O
+that	O
+are	O
+visible	O
+from	O
+a	O
+user	O
+'s	O
+viewpoint	O
+is	O
+one	O
+of	O
+the	O
+primary	O
+factors	O
+that	O
+affect	O
+server	O
+throughput	O
+and	O
+scalability	O
+.	O
+Specifically	O
+,	O
+performing	O
+real	O
+--	O
+time	O
+visibility	O
+tests	O
+in	O
+extremely	O
+dynamic	B-KEY
+virtual	I-KEY
+environments	I-KEY
+is	O
+a	O
+very	O
+challenging	O
+task	O
+as	O
+millions	O
+of	O
+objects	O
+and	O
+sub-millions	O
+of	O
+active	O
+users	O
+are	O
+moving	O
+and	O
+interacting	O
+.	O
+We	O
+recognize	O
+that	O
+the	O
+described	O
+challenges	O
+are	O
+closely	O
+related	O
+to	O
+a	O
+spatial	B-KEY
+database	I-KEY
+problem	O
+,	O
+and	O
+hence	O
+we	O
+map	O
+the	O
+moving	O
+geometry	O
+objects	O
+in	O
+the	O
+virtual	O
+space	O
+to	O
+a	O
+set	O
+of	O
+multi-dimensional	O
+objects	O
+in	O
+a	O
+spatial	B-KEY
+database	I-KEY
+while	O
+modeling	O
+each	O
+avatar	O
+both	O
+as	O
+a	O
+spatial	O
+object	O
+and	O
+a	O
+moving	O
+query	O
+.	O
+Unfortunately	O
+,	O
+existing	O
+spatial	B-KEY
+indexing	I-KEY
+methods	O
+are	O
+unsuitable	O
+for	O
+this	O
+kind	O
+of	O
+new	O
+environments	O
+.	O
+The	O
+main	O
+goal	O
+of	O
+this	O
+paper	O
+is	O
+to	O
+present	O
+an	O
+efficient	O
+spatial	B-KEY
+index	I-KEY
+structure	O
+that	O
+minimizes	O
+unexpected	O
+object	B-KEY
+popping	I-KEY
+and	O
+supports	O
+highly	O
+scalable	O
+real	O
+--	O
+time	O
+visibility	O
+determination	O
+.	O
+We	O
+then	O
+uncover	O
+many	O
+useful	O
+properties	O
+of	O
+this	O
+structure	O
+and	O
+compare	O
+the	O
+index	O
+structure	O
+with	O
+various	O
+spatial	B-KEY
+indexing	I-KEY
+methods	O
+in	O
+terms	O
+of	O
+query	O
+quality	O
+,	O
+system	O
+throughput	O
+,	O
+and	O
+resource	O
+utilization	O
+.	O
+We	O
+expect	O
+our	O
+approach	O
+to	O
+lay	O
+the	O
+groundwork	O
+for	O
+next	O
+--	O
+generation	O
+virtual	O
+frameworks	O
+that	O
+may	O
+merge	O
+into	O
+existing	O
+web	O
+--	O
+based	O
+services	O
+in	O
+the	O
+near	O
+future	O
+.	O
+∗	O
+This	O
+research	O
+has	O
+been	O
+funded	O
+in	O
+part	O
+by	O
+NSF	O
+grants	O
+EEC9529152	O
+-LRB-	O
+IMSC	O
+ERC	O
+-RRB-	O
+and	O
+IIS-0534761	O
+,	O
+and	O
+equipment	O
+gifts	O
+from	O
+Intel	O
+Corporation	O
+,	O
+Hewlett-Packard	O
+,	O
+Sun	O
+Microsystems	O
+and	O
+Raptor	O
+Networks	O
+Technology	O
+.	O
+Categories	O
+and	O
+Subject	O
+Descriptors	O
+:	O
+C.	O
+2.4	O
+-LSB-	O
+Computer	O
+--	O
+Com	O
+
+Combinatorial	B-KEY
+Agency	I-KEY
+ABSTRACT	O
+Much	O
+recent	O
+research	O
+concerns	O
+systems	O
+,	O
+such	O
+as	O
+the	O
+Internet	O
+,	O
+whose	O
+components	O
+are	O
+owned	O
+and	O
+operated	O
+by	O
+different	O
+parties	O
+,	O
+each	O
+with	O
+his	O
+own	O
+``	O
+selfish	O
+''	O
+goal	O
+.	O
+The	O
+field	O
+of	O
+Algorithmic	O
+Mechanism	O
+Design	O
+handles	O
+the	O
+issue	O
+of	O
+private	O
+information	O
+held	O
+by	O
+the	O
+different	O
+parties	O
+in	O
+such	O
+computational	O
+settings	O
+.	O
+This	O
+paper	O
+deals	O
+with	O
+a	O
+complementary	O
+problem	O
+in	O
+such	O
+settings	O
+:	O
+handling	O
+the	O
+``	O
+hidden	O
+actions	O
+''	O
+that	O
+are	O
+performed	O
+by	O
+the	O
+different	O
+parties	O
+.	O
+Our	O
+model	O
+is	O
+a	O
+combinatorial	O
+variant	O
+of	O
+the	O
+classical	O
+principalagent	O
+problem	O
+from	O
+economic	O
+theory	O
+.	O
+In	O
+our	O
+setting	O
+a	O
+principal	O
+must	O
+motivate	O
+a	O
+team	O
+of	O
+strategic	O
+agents	O
+to	O
+exert	O
+costly	O
+effort	O
+on	O
+his	O
+behalf	O
+,	O
+but	O
+their	O
+actions	O
+are	O
+hidden	O
+from	O
+him	O
+.	O
+Our	O
+focus	O
+is	O
+on	O
+cases	O
+where	O
+complex	O
+combinations	O
+of	O
+the	O
+efforts	O
+of	O
+the	O
+agents	O
+influence	O
+the	O
+outcome	O
+.	O
+The	O
+principal	O
+motivates	O
+the	O
+agents	O
+by	O
+offering	O
+to	O
+them	O
+a	O
+set	O
+of	O
+contracts	O
+,	O
+which	O
+together	O
+put	O
+the	O
+agents	O
+in	O
+an	O
+equilibrium	O
+point	O
+of	O
+the	O
+induced	O
+game	O
+.	O
+We	O
+present	O
+formal	O
+models	O
+for	O
+this	O
+setting	O
+,	O
+suggest	O
+and	O
+embark	O
+on	O
+an	O
+analysis	O
+of	O
+some	O
+basic	O
+issues	O
+,	O
+but	O
+leave	O
+many	O
+questions	O
+open	O
+.	O
+
+Strong	B-KEY
+Equilibrium	I-KEY
+in	O
+Cost	B-KEY
+Sharing	I-KEY
+Connection	I-KEY
+Games	I-KEY
+*	O
+ABSTRACT	O
+In	O
+this	O
+work	O
+we	O
+study	O
+cost	B-KEY
+sharing	I-KEY
+connection	I-KEY
+games	I-KEY
+,	O
+where	O
+each	O
+player	O
+has	O
+a	O
+source	O
+and	O
+sink	O
+he	O
+would	O
+like	O
+to	O
+connect	O
+,	O
+and	O
+the	O
+cost	B-KEY
+of	I-KEY
+the	I-KEY
+edges	I-KEY
+is	O
+either	O
+shared	O
+equally	O
+-LRB-	O
+fair	B-KEY
+connection	I-KEY
+games	I-KEY
+-RRB-	O
+or	O
+in	O
+an	O
+arbitrary	O
+way	O
+-LRB-	O
+general	B-KEY
+connection	I-KEY
+games	I-KEY
+-RRB-	O
+.	O
+We	O
+study	O
+the	O
+graph	B-KEY
+topologies	I-KEY
+that	O
+guarantee	O
+the	O
+existence	O
+of	O
+a	O
+strong	B-KEY
+equilibrium	I-KEY
+-LRB-	O
+where	O
+no	O
+coalition	B-KEY
+can	O
+improve	O
+the	O
+cost	O
+of	O
+each	O
+of	O
+its	O
+members	O
+-RRB-	O
+regardless	O
+of	O
+the	O
+specific	B-KEY
+costs	I-KEY
+on	O
+the	O
+edges	O
+.	O
+Our	O
+main	O
+existence	O
+results	O
+are	O
+the	O
+following	O
+:	O
+-LRB-	O
+1	O
+-RRB-	O
+For	O
+a	O
+single	B-KEY
+source	I-KEY
+and	I-KEY
+sink	I-KEY
+we	O
+show	O
+that	O
+there	O
+is	O
+always	O
+a	O
+strong	B-KEY
+equilibrium	I-KEY
+-LRB-	O
+both	O
+for	O
+fair	O
+and	O
+general	B-KEY
+connection	I-KEY
+games	I-KEY
+-RRB-	O
+.	O
+-LRB-	O
+2	O
+-RRB-	O
+For	O
+a	O
+single	B-KEY
+source	I-KEY
+multiple	I-KEY
+sinks	I-KEY
+we	O
+show	O
+that	O
+for	O
+a	O
+series	O
+parallel	O
+graph	O
+a	O
+strong	B-KEY
+equilibrium	I-KEY
+always	O
+exists	O
+-LRB-	O
+both	O
+for	O
+fair	O
+and	O
+general	B-KEY
+connection	I-KEY
+games	I-KEY
+-RRB-	O
+.	O
+-LRB-	O
+3	O
+-RRB-	O
+For	O
+multi	B-KEY
+source	I-KEY
+and	I-KEY
+sink	I-KEY
+we	O
+show	O
+that	O
+an	O
+extension	B-KEY
+parallel	I-KEY
+graph	I-KEY
+always	O
+admits	O
+a	O
+strong	B-KEY
+equilibrium	I-KEY
+in	O
+fair	B-KEY
+connection	I-KEY
+games	I-KEY
+.	O
+As	O
+for	O
+the	O
+quality	O
+of	O
+the	O
+strong	B-KEY
+equilibrium	I-KEY
+we	O
+show	O
+that	O
+in	O
+any	O
+fair	B-KEY
+connection	I-KEY
+games	I-KEY
+the	O
+cost	O
+of	O
+a	O
+strong	B-KEY
+equilibrium	I-KEY
+is	O
+Θ	O
+-LRB-	O
+log	O
+n	O
+-RRB-	O
+from	O
+the	O
+optimal	B-KEY
+solution	I-KEY
+,	O
+where	O
+n	O
+is	O
+the	O
+number	B-KEY
+of	I-KEY
+players	I-KEY
+.	O
+-LRB-	O
+This	O
+should	O
+be	O
+contrasted	O
+with	O
+the	O
+Ω	O
+-LRB-	O
+n	O
+-RRB-	O
+price	B-KEY
+of	I-KEY
+anarchy	I-KEY
+for	O
+the	O
+same	O
+setting	O
+.	O
+-RRB-	O
+For	O
+single	O
+source	O
+general	B-KEY
+connection	I-KEY
+games	I-KEY
+and	O
+single	O
+source	O
+single	O
+sink	O
+fair	B-KEY
+connection	I-KEY
+games	I-KEY
+,	O
+we	O
+show	O
+that	O
+a	O
+strong	B-KEY
+equilibrium	I-KEY
+is	O
+always	O
+an	O
+optimal	B-KEY
+solution	I-KEY
+.	O
+*	O
+Research	O
+supported	O
+in	O
+part	O
+by	O
+a	O
+grant	O
+of	O
+the	O
+Israel	O
+Science	O
+Foundation	O
+,	O
+Binational	O
+Science	O
+Foundation	O
+-LRB-	O
+BSF	O
+-RRB-	O
+,	O
+GermanIsraeli	O
+Foundation	O
+-LRB-	O
+GIF	O
+-RRB-	O
+,	O
+Lady	O
+Davis	O
+Fellowship	O
+,	O
+an	O
+IBM	O
+faculty	O
+award	O
+,	O
+and	O
+the	O
+IST	O
+Programme	O
+of	O
+the	O
+European	O
+Community	O
+,	O
+under	O
+the	O
+PASCAL	O
+Network	O
+of	O
+Excellence	O
+,	O
+IST-2002-506778	O
+.	O
+This	O
+publication	O
+only	O
+reflects	O
+the	O
+authors	O
+'	O
+views	O
+.	O
+
+Commitment	B-KEY
+and	O
+Extortion	B-KEY
+*	O
+ABSTRACT	O
+Making	O
+commitments	B-KEY
+,	O
+e.g.	O
+,	O
+through	O
+promises	O
+and	O
+threats	O
+,	O
+enables	O
+a	O
+player	O
+to	O
+exploit	O
+the	O
+strengths	O
+of	O
+his	O
+own	O
+strategic	B-KEY
+position	I-KEY
+as	O
+well	O
+as	O
+the	O
+weaknesses	O
+of	O
+that	O
+of	O
+his	O
+opponents	O
+.	O
+Which	O
+commitments	B-KEY
+a	O
+player	O
+can	O
+make	O
+with	O
+credibility	B-KEY
+depends	O
+on	O
+the	O
+circumstances	O
+.	O
+In	O
+some	O
+,	O
+a	O
+player	O
+can	O
+only	O
+commit	B-KEY
+to	O
+the	O
+performance	O
+of	O
+an	O
+action	O
+,	O
+in	O
+others	O
+,	O
+he	O
+can	O
+commit	B-KEY
+himself	O
+conditionally	O
+on	O
+the	O
+actions	O
+of	O
+the	O
+other	O
+players	O
+.	O
+Some	O
+situations	O
+even	O
+allow	O
+for	O
+commitments	B-KEY
+on	O
+commitments	B-KEY
+or	O
+for	O
+commitments	B-KEY
+to	O
+randomized	O
+actions	O
+.	O
+We	O
+explore	O
+the	O
+formal	O
+properties	O
+of	O
+these	O
+types	O
+of	O
+-LRB-	O
+conditional	O
+-RRB-	O
+commitment	B-KEY
+and	O
+their	O
+interrelationships	O
+.	O
+So	O
+as	O
+to	O
+preclude	O
+inconsistencies	O
+among	O
+conditional	O
+commitments	B-KEY
+,	O
+we	O
+assume	O
+an	O
+order	O
+in	O
+which	O
+the	O
+players	O
+make	O
+their	O
+commitments	B-KEY
+.	O
+Central	O
+to	O
+our	O
+analyses	O
+is	O
+the	O
+notion	O
+of	O
+an	O
+extortion	B-KEY
+,	O
+which	O
+we	O
+define	O
+,	O
+for	O
+a	O
+given	O
+order	O
+of	O
+the	O
+players	O
+,	O
+as	O
+a	O
+profile	O
+that	O
+contains	O
+,	O
+for	O
+each	O
+player	O
+,	O
+an	O
+optimal	O
+commitment	B-KEY
+given	O
+the	O
+commitments	B-KEY
+of	O
+the	O
+players	O
+that	O
+committed	B-KEY
+earlier	O
+.	O
+On	O
+this	O
+basis	O
+,	O
+we	O
+investigate	O
+for	O
+different	O
+commitment	B-KEY
+types	O
+whether	O
+it	O
+is	O
+advantageous	O
+to	O
+commit	B-KEY
+earlier	O
+rather	O
+than	O
+later	O
+,	O
+and	O
+how	O
+the	O
+outcomes	O
+obtained	O
+through	O
+extortions	B-KEY
+relate	O
+to	O
+backward	O
+induction	O
+and	O
+Pareto	B-KEY
+efficiency	I-KEY
+.	O
+
+Computing	O
+the	O
+Banzhaf	B-KEY
+Power	I-KEY
+Index	I-KEY
+in	O
+Network	O
+Flow	O
+Games	O
+ABSTRACT	O
+Preference	B-KEY
+aggregation	I-KEY
+is	O
+used	O
+in	O
+a	O
+variety	O
+of	O
+multiagent	B-KEY
+applications	I-KEY
+,	O
+and	O
+as	O
+a	O
+result	O
+,	O
+voting	B-KEY
+theory	O
+has	O
+become	O
+an	O
+important	O
+topic	O
+in	O
+multiagent	O
+system	O
+research	O
+.	O
+However	O
+,	O
+power	O
+indices	O
+-LRB-	O
+which	O
+reflect	O
+how	O
+much	O
+``	O
+real	O
+power	O
+''	O
+a	O
+voter	O
+has	O
+in	O
+a	O
+weighted	O
+voting	B-KEY
+system	O
+-RRB-	O
+have	O
+received	O
+relatively	O
+little	O
+attention	O
+,	O
+although	O
+they	O
+have	O
+long	O
+been	O
+studied	O
+in	O
+political	O
+science	O
+and	O
+economics	O
+.	O
+The	O
+Banzhaf	B-KEY
+power	I-KEY
+index	I-KEY
+is	O
+one	O
+of	O
+the	O
+most	O
+popular	O
+;	O
+it	O
+is	O
+also	O
+well-defined	O
+for	O
+any	O
+simple	O
+coalitional	O
+game	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+examine	O
+the	O
+computational	B-KEY
+complexity	I-KEY
+of	O
+calculating	O
+the	O
+Banzhaf	B-KEY
+power	I-KEY
+index	I-KEY
+within	O
+a	O
+particular	O
+multiagent	O
+domain	O
+,	O
+a	O
+network	O
+flow	O
+game	O
+.	O
+Agents	O
+control	O
+the	O
+edges	O
+of	O
+a	O
+graph	O
+;	O
+a	O
+coalition	O
+wins	O
+if	O
+it	O
+can	O
+send	O
+a	O
+flow	O
+of	O
+a	O
+given	O
+size	O
+from	O
+a	O
+source	O
+vertex	O
+to	O
+a	O
+target	O
+vertex	O
+.	O
+The	O
+relative	O
+power	O
+of	O
+each	O
+edge/agent	O
+reflects	O
+its	O
+significance	O
+in	O
+enabling	O
+such	O
+a	O
+flow	O
+,	O
+and	O
+in	O
+real-world	O
+networks	O
+could	O
+be	O
+used	O
+,	O
+for	O
+example	O
+,	O
+to	O
+allocate	O
+resources	O
+for	O
+maintaining	O
+parts	O
+of	O
+the	O
+network	O
+.	O
+We	O
+show	O
+that	O
+calculating	O
+the	O
+Banzhaf	B-KEY
+power	I-KEY
+index	I-KEY
+of	O
+each	O
+agent	O
+in	O
+this	O
+network	O
+flow	O
+domain	O
+is	O
+#P	O
+-	O
+complete	O
+.	O
+We	O
+also	O
+show	O
+that	O
+for	O
+some	O
+restricted	O
+network	O
+flow	O
+domains	O
+there	O
+exists	O
+a	O
+polynomial	O
+algorithm	O
+to	O
+calculate	O
+agents	O
+'	O
+Banzhaf	O
+power	O
+indices	O
+.	O
+
+Reasoning	O
+about	O
+Judgment	O
+and	O
+Preference	B-KEY
+Aggregation	I-KEY
+◦	O
+ABSTRACT	O
+Agents	O
+that	O
+must	O
+reach	O
+agreements	O
+with	O
+other	O
+agents	O
+need	O
+to	O
+reason	O
+about	O
+how	O
+their	O
+preferences	O
+,	O
+judgments	O
+,	O
+and	O
+beliefs	O
+might	O
+be	O
+aggregated	O
+with	O
+those	O
+of	O
+others	O
+by	O
+the	O
+social	O
+choice	O
+mechanisms	O
+that	O
+govern	O
+their	O
+interactions	O
+.	O
+The	O
+recently	O
+emerging	O
+field	O
+of	O
+judgment	B-KEY
+aggregation	I-KEY
+studies	O
+aggregation	O
+from	O
+a	O
+logical	O
+perspective	O
+,	O
+and	O
+considers	O
+how	O
+multiple	O
+sets	O
+of	O
+logical	O
+formulae	O
+can	O
+be	O
+aggregated	O
+to	O
+a	O
+single	O
+consistent	O
+set	O
+.	O
+As	O
+a	O
+special	O
+case	O
+,	O
+judgment	B-KEY
+aggregation	I-KEY
+can	O
+be	O
+seen	O
+to	O
+subsume	O
+classical	O
+preference	B-KEY
+aggregation	I-KEY
+.	O
+We	O
+present	O
+a	O
+modal	B-KEY
+logic	I-KEY
+that	O
+is	O
+intended	O
+to	O
+support	O
+reasoning	O
+about	O
+judgment	B-KEY
+aggregation	I-KEY
+scenarios	O
+-LRB-	O
+and	O
+hence	O
+,	O
+as	O
+a	O
+special	O
+case	O
+,	O
+about	O
+preference	B-KEY
+aggregation	I-KEY
+-RRB-	O
+:	O
+the	O
+logical	O
+language	O
+is	O
+interpreted	O
+directly	O
+in	O
+judgment	B-KEY
+aggregation	I-KEY
+rules	O
+.	O
+We	O
+present	O
+a	O
+sound	O
+and	O
+complete	B-KEY
+axiomatisation	I-KEY
+of	O
+such	O
+rules	O
+.	O
+We	O
+show	O
+that	O
+the	O
+logic	O
+can	O
+express	B-KEY
+aggregation	O
+rules	O
+such	O
+as	O
+majority	O
+voting	O
+;	O
+rule	O
+properties	O
+such	O
+as	O
+independence	O
+;	O
+and	O
+results	O
+such	O
+as	O
+the	O
+discursive	B-KEY
+paradox	I-KEY
+,	O
+Arrow	B-KEY
+'s	I-KEY
+theorem	I-KEY
+and	O
+Condorcet	O
+'s	O
+paradox	O
+--	O
+which	O
+are	O
+derivable	O
+as	O
+formal	O
+theorems	O
+of	O
+the	O
+logic	O
+.	O
+The	O
+logic	O
+is	O
+parameterised	O
+in	O
+such	O
+a	O
+way	O
+that	O
+it	O
+can	O
+be	O
+used	O
+as	O
+a	O
+general	O
+framework	O
+for	O
+comparing	O
+the	O
+logical	O
+properties	O
+of	O
+different	O
+types	O
+of	O
+aggregation	O
+--	O
+including	O
+classical	O
+preference	B-KEY
+aggregation	I-KEY
+.	O
+
+Robust	O
+Classification	O
+of	O
+Rare	O
+Queries	O
+Using	O
+Web	O
+Knowledge	O
+ABSTRACT	O
+We	O
+propose	O
+a	O
+methodology	O
+for	O
+building	O
+a	O
+practical	O
+robust	O
+query	B-KEY
+classification	I-KEY
+system	O
+that	O
+can	O
+identify	O
+thousands	O
+of	O
+query	O
+classes	O
+with	O
+reasonable	O
+accuracy	O
+,	O
+while	O
+dealing	O
+in	O
+realtime	O
+with	O
+the	O
+query	O
+volume	O
+of	O
+a	O
+commercial	O
+web	B-KEY
+search	I-KEY
+engine	O
+.	O
+We	O
+use	O
+a	O
+blind	O
+feedback	O
+technique	O
+:	O
+given	O
+a	O
+query	O
+,	O
+we	O
+determine	O
+its	O
+topic	O
+by	O
+classifying	O
+the	O
+web	B-KEY
+search	I-KEY
+results	O
+retrieved	O
+by	O
+the	O
+query	O
+.	O
+Motivated	O
+by	O
+the	O
+needs	O
+of	O
+search	B-KEY
+advertising	I-KEY
+,	O
+we	O
+primarily	O
+focus	O
+on	O
+rare	O
+queries	O
+,	O
+which	O
+are	O
+the	O
+hardest	O
+from	O
+the	O
+point	O
+of	O
+view	O
+of	O
+machine	B-KEY
+learning	I-KEY
+,	O
+yet	O
+in	O
+aggregation	O
+account	O
+for	O
+a	O
+considerable	O
+fraction	O
+of	O
+search	B-KEY
+engine	I-KEY
+traffic	O
+.	O
+Empirical	O
+evaluation	O
+confirms	O
+that	O
+our	O
+methodology	O
+yields	O
+a	O
+considerably	O
+higher	O
+classification	O
+accuracy	O
+than	O
+previously	O
+reported	O
+.	O
+We	O
+believe	O
+that	O
+the	O
+proposed	O
+methodology	O
+will	O
+lead	O
+to	O
+better	O
+matching	O
+of	O
+online	O
+ads	O
+to	O
+rare	O
+queries	O
+and	O
+overall	O
+to	O
+a	O
+better	O
+user	O
+experience	O
+.	O
+
+Collaboration	O
+Among	O
+a	O
+Satellite	B-KEY
+Swarm	I-KEY
+ABSTRACT	O
+The	O
+paper	O
+deals	O
+with	O
+on-board	B-KEY
+planning	I-KEY
+for	O
+a	O
+satellite	B-KEY
+swarm	I-KEY
+via	O
+communication	B-KEY
+and	I-KEY
+negotiation	I-KEY
+.	O
+We	O
+aim	O
+at	O
+defining	O
+individual	O
+behaviours	O
+that	O
+result	O
+in	O
+a	O
+global	O
+behaviour	O
+that	O
+meets	O
+the	O
+mission	O
+requirements	O
+.	O
+We	O
+will	O
+present	O
+the	O
+formalization	O
+of	O
+the	O
+problem	O
+,	O
+a	O
+communication	O
+protocol	O
+,	O
+a	O
+solving	O
+method	O
+based	O
+on	O
+reactive	B-KEY
+decision	I-KEY
+rules	I-KEY
+,	O
+and	O
+first	O
+results	O
+.	O
+
+An	O
+Advanced	B-KEY
+Bidding	I-KEY
+Agent	I-KEY
+for	O
+Advertisement	O
+Selection	O
+on	O
+Public	O
+Displays	O
+ABSTRACT	O
+In	O
+this	O
+paper	O
+we	O
+present	O
+an	O
+advanced	B-KEY
+bidding	I-KEY
+agent	I-KEY
+that	O
+participates	O
+in	O
+first-price	O
+sealed	O
+bid	O
+auctions	O
+to	O
+allocate	O
+advertising	O
+space	O
+on	O
+BluScreen	O
+--	O
+an	O
+experimental	O
+public	O
+advertisement	O
+system	O
+that	O
+detects	O
+users	O
+through	O
+the	O
+presence	O
+of	O
+their	O
+Bluetooth	O
+enabled	O
+devices	O
+.	O
+Our	O
+bidding	B-KEY
+agent	I-KEY
+is	O
+able	O
+to	O
+build	O
+probabilistic	B-KEY
+models	I-KEY
+of	O
+both	O
+the	O
+behaviour	O
+of	O
+users	O
+who	O
+view	O
+the	O
+adverts	O
+,	O
+and	O
+the	O
+auctions	B-KEY
+that	O
+it	O
+participates	O
+within	O
+.	O
+It	O
+then	O
+uses	O
+these	O
+models	O
+to	O
+maximise	O
+the	O
+exposure	O
+that	O
+its	O
+adverts	O
+receive	O
+.	O
+We	O
+evaluate	O
+the	O
+effectiveness	O
+of	O
+this	O
+bidding	B-KEY
+agent	I-KEY
+through	O
+simulation	O
+against	O
+a	O
+range	O
+of	O
+alternative	O
+selection	O
+mechanisms	O
+including	O
+a	O
+simple	O
+bidding	O
+strategy	O
+,	O
+random	O
+allocation	O
+,	O
+and	O
+a	O
+centralised	B-KEY
+optimal	I-KEY
+allocation	I-KEY
+with	O
+perfect	O
+foresight	O
+.	O
+Our	O
+bidding	B-KEY
+agent	I-KEY
+significantly	O
+outperforms	O
+both	O
+the	O
+simple	O
+bidding	O
+strategy	O
+and	O
+the	O
+random	O
+allocation	O
+,	O
+and	O
+in	O
+a	O
+mixed	O
+population	O
+of	O
+agents	O
+it	O
+is	O
+able	O
+to	O
+expose	O
+its	O
+adverts	O
+to	O
+25	O
+%	O
+more	O
+users	O
+than	O
+the	O
+simple	O
+bidding	O
+strategy	O
+.	O
+Moreover	O
+,	O
+its	O
+performance	O
+is	O
+within	O
+7.5	O
+%	O
+of	O
+that	O
+of	O
+the	O
+centralised	B-KEY
+optimal	I-KEY
+allocation	I-KEY
+despite	O
+the	O
+highly	O
+uncertain	O
+environment	O
+in	O
+which	O
+it	O
+must	O
+operate	O
+.	O
+
+The	O
+Impact	O
+of	O
+Caching	B-KEY
+on	O
+Search	O
+Engines	O
+ABSTRACT	O
+In	O
+this	O
+paper	O
+we	O
+study	O
+the	O
+trade-offs	O
+in	O
+designing	O
+efficient	O
+caching	B-KEY
+systems	O
+for	O
+Web	O
+search	O
+engines	O
+.	O
+We	O
+explore	O
+the	O
+impact	O
+of	O
+different	O
+approaches	O
+,	O
+such	O
+as	O
+static	O
+vs.	O
+dynamic	B-KEY
+caching	I-KEY
+,	O
+and	O
+caching	O
+query	O
+results	O
+vs.	O
+caching	O
+posting	O
+lists	O
+.	O
+Using	O
+a	O
+query	B-KEY
+log	I-KEY
+spanning	O
+a	O
+whole	O
+year	O
+we	O
+explore	O
+the	O
+limitations	O
+of	O
+caching	B-KEY
+and	O
+we	O
+demonstrate	O
+that	O
+caching	B-KEY
+posting	O
+lists	O
+can	O
+achieve	O
+higher	O
+hit	O
+rates	O
+than	O
+caching	O
+query	O
+answers	O
+.	O
+We	O
+propose	O
+a	O
+new	O
+algorithm	O
+for	O
+static	B-KEY
+caching	I-KEY
+of	O
+posting	O
+lists	O
+,	O
+which	O
+outperforms	O
+previous	O
+methods	O
+.	O
+We	O
+also	O
+study	O
+the	O
+problem	O
+of	O
+finding	O
+the	O
+optimal	O
+way	O
+to	O
+split	O
+the	O
+static	B-KEY
+cache	I-KEY
+between	O
+answers	O
+and	O
+posting	O
+lists	O
+.	O
+Finally	O
+,	O
+we	O
+measure	O
+how	O
+the	O
+changes	O
+in	O
+the	O
+query	B-KEY
+log	I-KEY
+affect	O
+the	O
+effectiveness	B-KEY
+of	I-KEY
+static	I-KEY
+caching	I-KEY
+,	O
+given	O
+our	O
+observation	O
+that	O
+the	O
+distribution	O
+of	O
+the	O
+queries	O
+changes	O
+slowly	O
+over	O
+time	O
+.	O
+Our	O
+results	O
+and	O
+observations	O
+are	O
+applicable	O
+to	O
+different	O
+levels	O
+of	O
+the	O
+data-access	B-KEY
+hierarchy	I-KEY
+,	O
+for	O
+instance	O
+,	O
+for	O
+a	O
+memory/disk	O
+layer	O
+or	O
+a	O
+broker/remote	O
+server	O
+layer	O
+.	O
+
+Revenue	B-KEY
+Analysis	O
+of	O
+a	O
+Family	O
+of	O
+Ranking	B-KEY
+Rules	I-KEY
+for	O
+Keyword	B-KEY
+Auctions	I-KEY
+ABSTRACT	O
+Keyword	B-KEY
+auctions	I-KEY
+lie	O
+at	O
+the	O
+core	O
+of	O
+the	O
+business	O
+models	O
+of	O
+today	O
+'s	O
+leading	O
+search	B-KEY
+engines	I-KEY
+.	O
+Advertisers	B-KEY
+bid	O
+for	O
+placement	O
+alongside	O
+search	O
+results	O
+,	O
+and	O
+are	O
+charged	O
+for	O
+clicks	O
+on	O
+their	O
+ads	O
+.	O
+Advertisers	B-KEY
+are	O
+typically	O
+ranked	O
+according	O
+to	O
+a	O
+score	O
+that	O
+takes	O
+into	O
+account	O
+their	O
+bids	O
+and	O
+potential	O
+clickthrough	O
+rates	O
+.	O
+We	O
+consider	O
+a	O
+family	O
+of	O
+ranking	B-KEY
+rules	I-KEY
+that	O
+contains	O
+those	O
+typically	O
+used	O
+to	O
+model	O
+Yahoo!	O
+and	O
+Google	O
+'s	O
+auction	O
+designs	O
+as	O
+special	O
+cases	O
+.	O
+We	O
+find	O
+that	O
+in	O
+general	O
+neither	O
+of	O
+these	O
+is	O
+necessarily	O
+revenue-optimal	O
+in	O
+equilibrium	O
+,	O
+and	O
+that	O
+the	O
+choice	O
+of	O
+ranking	B-KEY
+rule	I-KEY
+can	O
+be	O
+guided	O
+by	O
+considering	O
+the	O
+correlation	O
+between	O
+bidders	O
+'	O
+values	O
+and	O
+click-through	O
+rates	O
+.	O
+We	O
+propose	O
+a	O
+simple	O
+approach	O
+to	O
+determine	O
+a	O
+revenue-optimal	O
+ranking	B-KEY
+rule	I-KEY
+within	O
+our	O
+family	O
+,	O
+taking	O
+into	O
+account	O
+effects	O
+on	O
+advertiser	B-KEY
+satisfaction	O
+and	O
+user	O
+experience	O
+.	O
+We	O
+illustrate	O
+the	O
+approach	O
+using	O
+Monte-Carlo	O
+simulations	O
+based	O
+on	O
+distributions	O
+fitted	O
+to	O
+Yahoo!	O
+bid	O
+and	O
+click-through	O
+rate	O
+data	O
+for	O
+a	O
+high-volume	O
+keyword	O
+.	O
+
+Generalized	O
+Value	O
+Decomposition	O
+and	O
+Structured	O
+Multiattribute	B-KEY
+Auctions	I-KEY
+ABSTRACT	O
+Multiattribute	B-KEY
+auction	I-KEY
+mechanisms	O
+generally	O
+either	O
+remain	O
+agnostic	O
+about	O
+traders	O
+'	O
+preferences	O
+,	O
+or	O
+presume	O
+highly	O
+restrictive	O
+forms	O
+,	O
+such	O
+as	O
+full	O
+additivity	O
+.	O
+Real	O
+preferences	O
+often	O
+exhibit	O
+dependencies	O
+among	O
+attributes	O
+,	O
+yet	O
+may	O
+possess	O
+some	O
+structure	O
+that	O
+can	O
+be	O
+usefully	O
+exploited	O
+to	O
+streamline	O
+communication	O
+and	O
+simplify	O
+operation	O
+of	O
+a	O
+multiattribute	B-KEY
+auction	I-KEY
+.	O
+We	O
+develop	O
+such	O
+a	O
+structure	O
+using	O
+the	O
+theory	B-KEY
+of	I-KEY
+measurable	I-KEY
+value	I-KEY
+functions	I-KEY
+,	O
+a	O
+cardinal	O
+utility	O
+representation	O
+based	O
+on	O
+an	O
+underlying	O
+order	O
+over	O
+preference	O
+differences	O
+.	O
+A	O
+set	O
+of	O
+local	O
+conditional	O
+independence	O
+relations	O
+over	O
+such	O
+differences	O
+supports	O
+a	O
+generalized	O
+additive	O
+preference	O
+representation	O
+,	O
+which	O
+decomposes	O
+utility	O
+across	O
+overlapping	O
+clusters	O
+of	O
+related	O
+attributes	O
+.	O
+We	O
+introduce	O
+an	O
+iterative	O
+auction	B-KEY
+mechanism	O
+that	O
+maintains	O
+prices	O
+on	O
+local	O
+clusters	O
+of	O
+attributes	O
+rather	O
+than	O
+the	O
+full	O
+space	O
+of	O
+joint	O
+configurations	O
+.	O
+When	O
+traders	O
+'	O
+preferences	O
+are	O
+consistent	O
+with	O
+the	O
+auction	B-KEY
+'s	O
+generalized	O
+additive	O
+structure	O
+,	O
+the	O
+mechanism	O
+produces	O
+approximately	O
+optimal	O
+allocations	O
+,	O
+at	O
+approximate	O
+VCG	O
+prices	O
+.	O
+
+Bidding	O
+Optimally	O
+in	O
+Concurrent	O
+Second-Price	O
+Auctions	O
+of	O
+Perfectly	O
+Substitutable	O
+Goods	O
+ABSTRACT	O
+We	O
+derive	O
+optimal	B-KEY
+bidding	I-KEY
+strategies	I-KEY
+for	O
+a	O
+global	B-KEY
+bidding	I-KEY
+agent	I-KEY
+that	O
+participates	O
+in	O
+multiple	O
+,	O
+simultaneous	O
+second-price	O
+auctions	O
+with	O
+perfect	B-KEY
+substitutes	I-KEY
+.	O
+We	O
+first	O
+consider	O
+a	O
+model	O
+where	O
+all	O
+other	O
+bidders	O
+are	O
+local	O
+and	O
+participate	O
+in	O
+a	O
+single	O
+auction	O
+.	O
+For	O
+this	O
+case	O
+,	O
+we	O
+prove	O
+that	O
+,	O
+assuming	O
+free	O
+disposal	O
+,	O
+the	O
+global	O
+bidder	O
+should	O
+always	O
+place	O
+non-zero	O
+bids	O
+in	O
+all	O
+available	O
+auctions	O
+,	O
+irrespective	O
+of	O
+the	O
+local	O
+bidders	O
+'	O
+valuation	O
+distribution	O
+.	O
+Furthermore	O
+,	O
+for	O
+non-decreasing	B-KEY
+valuation	I-KEY
+distributions	I-KEY
+,	O
+we	O
+prove	O
+that	O
+the	O
+problem	O
+of	O
+finding	O
+the	O
+optimal	O
+bids	O
+reduces	O
+to	O
+two	O
+dimensions	O
+.	O
+These	O
+results	O
+hold	O
+both	O
+in	O
+the	O
+case	O
+where	O
+the	O
+number	O
+of	O
+local	O
+bidders	O
+is	O
+known	O
+and	O
+when	O
+this	O
+number	O
+is	O
+determined	O
+by	O
+a	O
+Poisson	O
+distribution	O
+.	O
+This	O
+analysis	O
+extends	O
+to	O
+online	B-KEY
+markets	I-KEY
+where	O
+,	O
+typically	O
+,	O
+auctions	O
+occur	O
+both	O
+concurrently	O
+and	O
+sequentially	O
+.	O
+In	O
+addition	O
+,	O
+by	O
+combining	O
+analytical	O
+and	O
+simulation	O
+results	O
+,	O
+we	O
+demonstrate	O
+that	O
+similar	O
+results	O
+hold	O
+in	O
+the	O
+case	O
+of	O
+several	O
+global	O
+bidders	O
+,	O
+provided	O
+that	O
+the	O
+market	O
+consists	O
+of	O
+both	O
+global	O
+and	O
+local	O
+bidders	O
+.	O
+Finally	O
+,	O
+we	O
+address	O
+the	O
+efficiency	O
+of	O
+the	O
+overall	O
+market	O
+,	O
+and	O
+show	O
+that	O
+information	O
+about	O
+the	O
+number	O
+of	O
+local	O
+bidders	O
+is	O
+an	O
+important	O
+determinant	O
+for	O
+the	O
+way	O
+in	O
+which	O
+a	O
+global	O
+bidder	O
+affects	O
+efficiency	O
+.	O
+
+Learning	B-KEY
+From	I-KEY
+Revealed	I-KEY
+Preference	I-KEY
+ABSTRACT	O
+A	O
+sequence	O
+of	O
+prices	O
+and	O
+demands	O
+are	O
+rationalizable	B-KEY
+if	O
+there	O
+exists	O
+a	O
+concave	O
+,	O
+continuous	O
+and	O
+monotone	O
+utility	O
+function	O
+such	O
+that	O
+the	O
+demands	O
+are	O
+the	O
+maximizers	O
+of	O
+the	O
+utility	O
+function	O
+over	O
+the	O
+budget	O
+set	O
+corresponding	O
+to	O
+the	O
+price	O
+.	O
+Afriat	O
+-LSB-	O
+1	O
+-RSB-	O
+presented	O
+necessary	O
+and	O
+sufficient	O
+conditions	O
+for	O
+a	O
+finite	O
+sequence	O
+to	O
+be	O
+rationalizable	B-KEY
+.	O
+Varian	O
+-LSB-	O
+20	O
+-RSB-	O
+and	O
+later	O
+Blundell	O
+et	O
+al.	O
+-LSB-	O
+3	O
+,	O
+4	O
+-RSB-	O
+continued	O
+this	O
+line	O
+of	O
+work	O
+studying	O
+nonparametric	O
+methods	O
+to	O
+forecasts	B-KEY
+demand	O
+.	O
+Their	O
+results	O
+essentially	O
+characterize	O
+learnability	O
+of	O
+degenerate	O
+classes	O
+of	O
+demand	B-KEY
+functions	I-KEY
+and	O
+therefore	O
+fall	O
+short	O
+of	O
+giving	O
+a	O
+general	O
+degree	O
+of	O
+confidence	O
+in	O
+the	O
+forecast	B-KEY
+.	O
+The	O
+present	O
+paper	O
+complements	O
+this	O
+line	O
+of	O
+research	O
+by	O
+introducing	O
+a	O
+statistical	O
+model	O
+and	O
+a	O
+measure	O
+of	O
+complexity	O
+through	O
+which	O
+we	O
+are	O
+able	O
+to	O
+study	O
+the	O
+learnability	O
+of	O
+classes	O
+of	O
+demand	B-KEY
+functions	I-KEY
+and	O
+derive	O
+a	O
+degree	O
+of	O
+confidence	O
+in	O
+the	O
+forecasts	B-KEY
+.	O
+Our	O
+results	O
+show	O
+that	O
+the	O
+class	O
+of	O
+all	O
+demand	B-KEY
+functions	I-KEY
+has	O
+unbounded	O
+complexity	O
+and	O
+therefore	O
+is	O
+not	O
+learnable	O
+,	O
+but	O
+that	O
+there	O
+exist	O
+interesting	O
+and	O
+potentially	O
+useful	O
+classes	O
+that	O
+are	O
+learnable	O
+from	O
+finite	O
+samples	O
+.	O
+We	O
+also	O
+present	O
+a	O
+learning	O
+algorithm	O
+that	O
+is	O
+an	O
+adaptation	O
+of	O
+a	O
+new	O
+proof	O
+of	O
+Afriat	O
+'s	O
+theorem	O
+due	O
+to	O
+Teo	O
+and	O
+Vohra	O
+-LSB-	O
+17	O
+-RSB-	O
+.	O
+
+Clearing	O
+Algorithms	O
+for	O
+Barter	B-KEY
+Exchange	B-KEY
+Markets	O
+:	O
+Enabling	O
+Nationwide	O
+Kidney	O
+Exchanges	B-KEY
+ABSTRACT	O
+In	O
+barter-exchange	O
+markets	O
+,	O
+agents	O
+seek	O
+to	O
+swap	O
+their	O
+items	O
+with	O
+one	O
+another	O
+,	O
+in	O
+order	O
+to	O
+improve	O
+their	O
+own	O
+utilities	O
+.	O
+These	O
+swaps	O
+consist	O
+of	O
+cycles	O
+of	O
+agents	O
+,	O
+with	O
+each	O
+agent	O
+receiving	O
+the	O
+item	O
+of	O
+the	O
+next	O
+agent	O
+in	O
+the	O
+cycle	O
+.	O
+We	O
+focus	O
+mainly	O
+on	O
+the	O
+upcoming	O
+national	O
+kidney-exchange	O
+market	O
+,	O
+where	O
+patients	O
+with	O
+kidney	O
+disease	O
+can	O
+obtain	O
+compatible	O
+donors	O
+by	O
+swapping	O
+their	O
+own	O
+willing	O
+but	O
+incompatible	O
+donors	O
+.	O
+With	O
+over	O
+70,000	O
+patients	O
+already	O
+waiting	O
+for	O
+a	O
+cadaver	O
+kidney	O
+in	O
+the	O
+US	O
+,	O
+this	O
+market	O
+is	O
+seen	O
+as	O
+the	O
+only	O
+ethical	O
+way	O
+to	O
+significantly	O
+reduce	O
+the	O
+4,000	O
+deaths	O
+per	O
+year	O
+attributed	O
+to	O
+kidney	O
+disease	O
+.	O
+The	O
+clearing	O
+problem	O
+involves	O
+finding	O
+a	O
+social	O
+welfare	O
+maximizing	O
+exchange	B-KEY
+when	O
+the	O
+maximum	O
+length	O
+of	O
+a	O
+cycle	O
+is	O
+fixed	O
+.	O
+Long	O
+cycles	O
+are	O
+forbidden	O
+,	O
+since	O
+,	O
+for	O
+incentive	O
+reasons	O
+,	O
+all	O
+transplants	B-KEY
+in	O
+a	O
+cycle	O
+must	O
+be	O
+performed	O
+simultaneously	O
+.	O
+Also	O
+,	O
+in	O
+barter-exchanges	O
+generally	O
+,	O
+more	O
+agents	O
+are	O
+affected	O
+if	O
+one	O
+drops	O
+out	O
+of	O
+a	O
+longer	O
+cycle	O
+.	O
+We	O
+prove	O
+that	O
+the	O
+clearing	O
+problem	O
+with	O
+this	O
+cycle-length	O
+constraint	O
+is	O
+NP-hard	O
+.	O
+Solving	O
+it	O
+exactly	O
+is	O
+one	O
+of	O
+the	O
+main	O
+challenges	O
+in	O
+establishing	O
+a	O
+national	O
+kidney	O
+exchange	B-KEY
+.	O
+We	O
+present	O
+the	O
+first	O
+algorithm	O
+capable	O
+of	O
+clearing	O
+these	O
+markets	O
+on	O
+a	O
+nationwide	O
+scale	O
+.	O
+The	O
+key	O
+is	O
+incremental	O
+problem	O
+formulation	O
+.	O
+We	O
+adapt	O
+two	O
+paradigms	O
+for	O
+the	O
+task	O
+:	O
+constraint	O
+generation	O
+and	O
+column	B-KEY
+generation	I-KEY
+.	O
+For	O
+each	O
+,	O
+we	O
+develop	O
+techniques	O
+that	O
+dramatically	O
+improve	O
+both	O
+runtime	O
+and	O
+memory	O
+usage	O
+.	O
+We	O
+conclude	O
+that	O
+column	B-KEY
+generation	I-KEY
+scales	O
+drastically	O
+better	O
+than	O
+constraint	O
+generation	O
+.	O
+Our	O
+algorithm	O
+also	O
+supports	O
+several	O
+generalizations	O
+,	O
+as	O
+demanded	O
+by	O
+real-world	O
+kidney	O
+exchanges	B-KEY
+.	O
+Our	O
+algorithm	O
+replaced	O
+CPLEX	O
+as	O
+the	O
+clearing	O
+algorithm	O
+of	O
+the	O
+Alliance	O
+for	O
+Paired	O
+Donation	O
+,	O
+one	O
+of	O
+the	O
+leading	O
+kidney	O
+exchanges	B-KEY
+.	O
+The	O
+match	B-KEY
+runs	O
+are	O
+conducted	O
+every	O
+two	O
+weeks	O
+and	O
+transplants	B-KEY
+based	O
+on	O
+our	O
+optimizations	O
+have	O
+already	O
+been	O
+conducted	O
+.	O
+
+Learn	O
+from	O
+Web	O
+Search	O
+Logs	O
+to	O
+Organize	O
+Search	O
+Results	O
+ABSTRACT	O
+Effective	O
+organization	O
+of	O
+search	O
+results	O
+is	O
+critical	O
+for	O
+improving	O
+the	O
+utility	O
+of	O
+any	O
+search	O
+engine	O
+.	O
+Clustering	O
+search	O
+results	O
+is	O
+an	O
+effective	O
+way	O
+to	O
+organize	O
+search	O
+results	O
+,	O
+which	O
+allows	O
+a	O
+user	O
+to	O
+navigate	O
+into	O
+relevant	O
+documents	O
+quickly	O
+.	O
+However	O
+,	O
+two	O
+deficiencies	O
+of	O
+this	O
+approach	O
+make	O
+it	O
+not	O
+always	O
+work	O
+well	O
+:	O
+-LRB-	O
+1	O
+-RRB-	O
+the	O
+clusters	O
+discovered	O
+do	O
+not	O
+necessarily	O
+correspond	O
+to	O
+the	O
+interesting	B-KEY
+aspects	I-KEY
+of	O
+a	O
+topic	O
+from	O
+the	O
+user	O
+'s	O
+perspective	O
+;	O
+and	O
+-LRB-	O
+2	O
+-RRB-	O
+the	O
+cluster	O
+labels	O
+generated	O
+are	O
+not	O
+informative	O
+enough	O
+to	O
+allow	O
+a	O
+user	O
+to	O
+identify	O
+the	O
+right	O
+cluster	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+propose	O
+to	O
+address	O
+these	O
+two	O
+deficiencies	O
+by	O
+-LRB-	O
+1	O
+-RRB-	O
+learning	O
+``	O
+interesting	B-KEY
+aspects	I-KEY
+''	O
+of	O
+a	O
+topic	O
+from	O
+Web	O
+search	O
+logs	O
+and	O
+organizing	O
+search	O
+results	O
+accordingly	O
+;	O
+and	O
+-LRB-	O
+2	O
+-RRB-	O
+generating	O
+more	O
+meaningful	B-KEY
+cluster	I-KEY
+labels	I-KEY
+using	O
+past	B-KEY
+query	I-KEY
+words	O
+entered	O
+by	O
+users	O
+.	O
+We	O
+evaluate	O
+our	O
+proposed	O
+method	O
+on	O
+a	O
+commercial	O
+search	B-KEY
+engine	I-KEY
+log	I-KEY
+data	O
+.	O
+Compared	O
+with	O
+the	O
+traditional	O
+methods	O
+of	O
+clustering	O
+search	O
+results	O
+,	O
+our	O
+method	O
+can	O
+give	O
+better	O
+result	O
+organization	O
+and	O
+more	O
+meaningful	O
+labels	O
+.	O
+
+New	B-KEY
+Event	I-KEY
+Detection	I-KEY
+Based	O
+on	O
+Indexing-tree	O
+and	O
+Named	B-KEY
+Entity	I-KEY
+ABSTRACT	O
+New	B-KEY
+Event	I-KEY
+Detection	I-KEY
+-LRB-	O
+NED	O
+-RRB-	O
+aims	O
+at	O
+detecting	O
+from	O
+one	O
+or	O
+multiple	O
+streams	O
+of	O
+news	O
+stories	O
+that	O
+which	O
+one	O
+is	O
+reported	O
+on	O
+a	O
+new	O
+event	O
+-LRB-	O
+i.e.	O
+not	O
+reported	O
+previously	O
+-RRB-	O
+.	O
+With	O
+the	O
+overwhelming	O
+volume	O
+of	O
+news	O
+available	O
+today	O
+,	O
+there	O
+is	O
+an	O
+increasing	O
+need	O
+for	O
+a	O
+NED	O
+system	O
+which	O
+is	O
+able	O
+to	O
+detect	O
+new	O
+events	O
+more	O
+efficiently	O
+and	O
+accurately	O
+.	O
+In	O
+this	O
+paper	O
+we	O
+propose	O
+a	O
+new	O
+NED	O
+model	O
+to	O
+speed	O
+up	O
+the	O
+NED	O
+task	O
+by	O
+using	O
+news	O
+indexing-tree	O
+dynamically	O
+.	O
+Moreover	O
+,	O
+based	O
+on	O
+the	O
+observation	O
+that	O
+terms	O
+of	O
+different	O
+types	O
+have	O
+different	O
+effects	O
+for	O
+NED	O
+task	O
+,	O
+two	O
+term	B-KEY
+reweighting	I-KEY
+approaches	I-KEY
+are	O
+proposed	O
+to	O
+improve	O
+NED	B-KEY
+accuracy	I-KEY
+.	O
+In	O
+the	O
+first	O
+approach	O
+,	O
+we	O
+propose	O
+to	O
+adjust	O
+term	B-KEY
+weights	I-KEY
+dynamically	O
+based	O
+on	O
+previous	O
+story	O
+clusters	O
+and	O
+in	O
+the	O
+second	O
+approach	O
+,	O
+we	O
+propose	O
+to	O
+employ	O
+statistics	B-KEY
+on	O
+training	B-KEY
+data	I-KEY
+to	O
+learn	O
+the	O
+named	B-KEY
+entity	I-KEY
+reweighting	O
+model	O
+for	O
+each	O
+class	B-KEY
+of	I-KEY
+stories	I-KEY
+.	O
+Experimental	O
+results	O
+on	O
+two	O
+Linguistic	B-KEY
+Data	I-KEY
+Consortium	I-KEY
+-LRB-	O
+LDC	O
+-RRB-	O
+datasets	O
+TDT2	O
+and	O
+TDT3	O
+show	O
+that	O
+the	O
+proposed	O
+model	O
+can	O
+improve	O
+both	O
+efficiency	O
+and	O
+accuracy	O
+of	O
+NED	O
+task	O
+significantly	O
+,	O
+compared	O
+to	O
+the	O
+baseline	B-KEY
+system	I-KEY
+and	O
+other	O
+existing	B-KEY
+systems	I-KEY
+.	O
+
+Resolving	O
+Conflict	O
+and	O
+Inconsistency	O
+in	O
+Norm-Regulated	O
+Virtual	B-KEY
+Organizations	I-KEY
+ABSTRACT	O
+Norm-governed	O
+virtual	B-KEY
+organizations	I-KEY
+define	O
+,	O
+govern	O
+and	O
+facilitate	O
+coordinated	O
+resource	O
+sharing	O
+and	O
+problem	O
+solving	O
+in	O
+societies	O
+of	O
+agents	B-KEY
+.	O
+With	O
+an	O
+explicit	O
+account	O
+of	O
+norms	O
+,	O
+openness	O
+in	O
+virtual	B-KEY
+organizations	I-KEY
+can	O
+be	O
+achieved	O
+:	O
+new	O
+components	O
+,	O
+designed	O
+by	O
+various	O
+parties	O
+,	O
+can	O
+be	O
+seamlessly	O
+accommodated	O
+.	O
+We	O
+focus	O
+on	O
+virtual	B-KEY
+organizations	I-KEY
+realised	O
+as	O
+multi-agent	O
+systems	O
+,	O
+in	O
+which	O
+human	O
+and	O
+software	O
+agents	B-KEY
+interact	O
+to	O
+achieve	O
+individual	O
+and	O
+global	O
+goals	O
+.	O
+However	O
+,	O
+any	O
+realistic	O
+account	O
+of	O
+norms	O
+should	O
+address	O
+their	O
+dynamic	O
+nature	O
+:	O
+norms	O
+will	O
+change	O
+as	O
+agents	B-KEY
+interact	O
+with	O
+each	O
+other	O
+and	O
+their	O
+environment	O
+.	O
+Due	O
+to	O
+the	O
+changing	O
+nature	O
+of	O
+norms	O
+or	O
+due	O
+to	O
+norms	O
+stemming	O
+from	O
+different	O
+virtual	B-KEY
+organizations	I-KEY
+,	O
+there	O
+will	O
+be	O
+situations	O
+when	O
+an	O
+action	O
+is	O
+simultaneously	O
+permitted	O
+and	O
+prohibited	O
+,	O
+that	O
+is	O
+,	O
+a	O
+conflict	O
+arises	O
+.	O
+Likewise	O
+,	O
+there	O
+will	O
+be	O
+situations	O
+when	O
+an	O
+action	O
+is	O
+both	O
+obliged	O
+and	O
+prohibited	O
+,	O
+that	O
+is	O
+,	O
+an	O
+inconsistency	O
+arises	O
+.	O
+We	O
+introduce	O
+an	O
+approach	O
+,	O
+based	O
+on	O
+first-order	O
+unification	O
+,	O
+to	O
+detect	O
+and	O
+resolve	O
+such	O
+conflicts	O
+and	O
+inconsistencies	O
+.	O
+In	O
+our	O
+proposed	O
+solution	O
+,	O
+we	O
+annotate	O
+a	O
+norm	O
+with	O
+the	O
+set	O
+of	O
+values	O
+their	O
+variables	O
+should	O
+not	O
+have	O
+in	O
+order	O
+to	O
+avoid	O
+a	O
+conflict	O
+or	O
+an	O
+inconsistency	O
+with	O
+another	O
+norm	O
+.	O
+Our	O
+approach	O
+neatly	O
+accommodates	O
+the	O
+domain-dependent	O
+interrelations	O
+among	O
+actions	O
+and	O
+the	O
+indirect	O
+conflicts/inconsistencies	O
+these	O
+may	O
+cause	O
+.	O
+More	O
+generally	O
+,	O
+we	O
+can	O
+capture	O
+a	O
+useful	O
+notion	O
+of	O
+inter-agent	O
+-LRB-	O
+and	O
+inter-role	O
+-RRB-	O
+delegation	O
+of	O
+actions	O
+and	O
+norms	O
+associated	O
+to	O
+them	O
+,	O
+and	O
+use	O
+it	O
+to	O
+address	O
+conflicts/inconsistencies	O
+caused	O
+by	O
+action	O
+delegation	O
+.	O
+We	O
+illustrate	O
+our	O
+approach	O
+with	O
+an	O
+e-Science	O
+example	O
+in	O
+which	O
+agents	B-KEY
+support	O
+Grid	O
+services	O
+.	O
+
+Regularized	B-KEY
+Clustering	O
+for	O
+Documents	O
+*	O
+ABSTRACT	O
+In	O
+recent	O
+years	O
+,	O
+document	B-KEY
+clustering	I-KEY
+has	O
+been	O
+receiving	O
+more	O
+and	O
+more	O
+attentions	O
+as	O
+an	O
+important	O
+and	O
+fundamental	O
+technique	O
+for	O
+unsupervised	O
+document	O
+organization	O
+,	O
+automatic	O
+topic	O
+extraction	O
+,	O
+and	O
+fast	O
+information	O
+retrieval	O
+or	O
+filtering	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+propose	O
+a	O
+novel	O
+method	O
+for	O
+clustering	O
+documents	O
+using	O
+regularization	B-KEY
+.	O
+Unlike	O
+traditional	O
+globally	B-KEY
+regularized	I-KEY
+clustering	O
+methods	O
+,	O
+our	O
+method	O
+first	O
+construct	O
+a	O
+local	O
+regularized	O
+linear	O
+label	O
+predictor	O
+for	O
+each	O
+document	O
+vector	O
+,	O
+and	O
+then	O
+combine	O
+all	O
+those	O
+local	O
+regularizers	O
+with	O
+a	O
+global	O
+smoothness	O
+regularizer	O
+.	O
+So	O
+we	O
+call	O
+our	O
+algorithm	O
+Clustering	O
+with	O
+Local	O
+and	O
+Global	B-KEY
+Regularization	I-KEY
+-LRB-	O
+CLGR	O
+-RRB-	O
+.	O
+We	O
+will	O
+show	O
+that	O
+the	O
+cluster	O
+memberships	O
+of	O
+the	O
+documents	O
+can	O
+be	O
+achieved	O
+by	O
+eigenvalue	O
+decomposition	O
+of	O
+a	O
+sparse	O
+symmetric	O
+matrix	O
+,	O
+which	O
+can	O
+be	O
+efficiently	O
+solved	O
+by	O
+iterative	O
+methods	O
+.	O
+Finally	O
+our	O
+experimental	O
+evaluations	O
+on	O
+several	O
+datasets	O
+are	O
+presented	O
+to	O
+show	O
+the	O
+superiorities	O
+of	O
+CLGR	O
+over	O
+traditional	O
+document	B-KEY
+clustering	I-KEY
+methods	O
+.	O
+
+Implementation	O
+and	O
+Performance	O
+Evaluation	O
+of	O
+CONFLEX-G	B-KEY
+:	O
+Grid-enabled	O
+Molecular	O
+Conformational	B-KEY
+Space	I-KEY
+Search	I-KEY
+Program	O
+with	O
+OmniRPC	B-KEY
+ABSTRACT	O
+CONFLEX-G	B-KEY
+is	O
+the	O
+grid-enabled	O
+version	O
+of	O
+a	O
+molecular	O
+conformational	B-KEY
+space	I-KEY
+search	I-KEY
+program	O
+called	O
+CONFLEX	O
+.	O
+We	O
+have	O
+implemented	O
+CONFLEX-G	B-KEY
+using	O
+a	O
+grid	B-KEY
+RPC	I-KEY
+system	I-KEY
+called	O
+OmniRPC	B-KEY
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+report	O
+the	O
+performance	O
+of	O
+CONFLEX-G	B-KEY
+in	O
+a	O
+grid	O
+testbed	O
+of	O
+several	O
+geographically	O
+distributed	O
+PC	B-KEY
+clusters	I-KEY
+.	O
+In	O
+order	O
+to	O
+explore	O
+many	O
+conformation	O
+of	O
+large	O
+bio-molecules	B-KEY
+,	O
+CONFLEX-G	B-KEY
+generates	O
+trial	O
+structures	O
+of	O
+the	O
+molecules	O
+and	O
+allocates	O
+jobs	O
+to	O
+optimize	O
+a	O
+trial	O
+structure	O
+with	O
+a	O
+reliable	O
+molecular	B-KEY
+mechanics	I-KEY
+method	O
+in	O
+the	O
+grid	O
+.	O
+OmniRPC	B-KEY
+provides	O
+a	O
+restricted	O
+persistence	O
+model	O
+to	O
+support	O
+the	O
+parametric	O
+search	O
+applications	O
+.	O
+In	O
+this	O
+model	O
+,	O
+when	O
+the	O
+initialization	B-KEY
+procedure	I-KEY
+is	O
+defined	O
+in	O
+the	O
+RPC	B-KEY
+module	I-KEY
+,	O
+the	O
+module	O
+is	O
+automatically	O
+initialized	O
+at	O
+the	O
+time	O
+of	O
+invocation	O
+by	O
+calling	O
+the	O
+initialization	B-KEY
+procedure	I-KEY
+.	O
+This	O
+can	O
+eliminate	O
+unnecessary	O
+communication	O
+and	O
+initialization	O
+at	O
+each	O
+call	O
+in	O
+CONFLEX-G	B-KEY
+.	O
+CONFLEXG	O
+can	O
+achieve	O
+performance	O
+comparable	O
+to	O
+CONFLEX	O
+MPI	O
+and	O
+can	O
+exploit	O
+more	O
+computing	O
+resources	O
+by	O
+allowing	O
+the	O
+use	O
+of	O
+a	O
+cluster	O
+of	O
+multiple	O
+clusters	O
+in	O
+the	O
+grid	O
+.	O
+The	O
+experimental	O
+result	O
+shows	O
+that	O
+CONFLEX-G	B-KEY
+achieved	O
+a	O
+speedup	O
+of	O
+56.5	O
+times	O
+in	O
+the	O
+case	O
+of	O
+the	O
+1BL1	O
+molecule	O
+,	O
+where	O
+the	O
+molecule	O
+consists	O
+of	O
+a	O
+large	O
+number	O
+of	O
+atoms	O
+,	O
+and	O
+each	O
+trial	O
+structure	O
+optimization	O
+requires	O
+significant	O
+time	O
+.	O
+The	O
+load	O
+imbalance	O
+of	O
+the	O
+optimization	O
+time	O
+of	O
+the	O
+trial	O
+structure	O
+may	O
+also	O
+cause	O
+performance	O
+degradation	O
+.	O
+
+Computation	O
+in	O
+a	O
+Distributed	B-KEY
+Information	I-KEY
+Market	O
+∗	O
+ABSTRACT	O
+According	O
+to	O
+economic	B-KEY
+theory	I-KEY
+--	O
+supported	O
+by	O
+empirical	B-KEY
+and	I-KEY
+laboratory	I-KEY
+evidence	I-KEY
+--	O
+the	O
+equilibrium	B-KEY
+price	I-KEY
+of	O
+a	O
+financial	B-KEY
+security	I-KEY
+reflects	O
+all	O
+of	O
+the	O
+information	O
+regarding	O
+the	O
+security	O
+'s	O
+value	O
+.	O
+We	O
+investigate	O
+the	O
+computational	B-KEY
+process	I-KEY
+on	O
+the	O
+path	B-KEY
+toward	I-KEY
+equilibrium	I-KEY
+,	O
+where	O
+information	O
+distributed	O
+among	O
+traders	B-KEY
+is	O
+revealed	O
+step-by-step	O
+over	O
+time	O
+and	O
+incorporated	O
+into	O
+the	O
+market	B-KEY
+price	I-KEY
+.	O
+We	O
+develop	O
+a	O
+simplified	B-KEY
+model	I-KEY
+of	O
+an	O
+information	B-KEY
+market	I-KEY
+,	O
+along	O
+with	O
+trading	B-KEY
+strategies	I-KEY
+,	O
+in	O
+order	O
+to	O
+formalize	O
+the	O
+computational	B-KEY
+properties	I-KEY
+of	I-KEY
+the	I-KEY
+process	I-KEY
+.	O
+We	O
+show	O
+that	O
+securities	B-KEY
+whose	O
+payoffs	B-KEY
+can	O
+not	O
+be	O
+expressed	O
+as	O
+weighted	O
+threshold	B-KEY
+functions	I-KEY
+of	O
+distributed	O
+input	O
+bits	O
+are	O
+not	O
+guaranteed	O
+to	O
+converge	O
+to	O
+the	O
+proper	O
+equilibrium	O
+predicted	O
+by	O
+economic	B-KEY
+theory	I-KEY
+.	O
+On	O
+the	O
+other	O
+hand	O
+,	O
+securities	B-KEY
+whose	O
+payoffs	B-KEY
+are	O
+threshold	B-KEY
+functions	I-KEY
+are	O
+guaranteed	O
+to	O
+converge	O
+,	O
+for	O
+all	O
+prior	O
+probability	B-KEY
+distributions	I-KEY
+.	O
+Moreover	O
+,	O
+these	O
+threshold	O
+securities	B-KEY
+converge	O
+in	O
+at	O
+most	O
+n	O
+rounds	B-KEY
+,	O
+where	O
+n	O
+is	O
+the	O
+number	B-KEY
+of	I-KEY
+bits	I-KEY
+of	O
+distributed	B-KEY
+information	I-KEY
+.	O
+We	O
+also	O
+prove	O
+a	O
+lower	B-KEY
+bound	I-KEY
+,	O
+showing	O
+a	O
+type	O
+of	O
+threshold	O
+security	B-KEY
+that	O
+requires	O
+at	O
+least	O
+n/2	O
+rounds	B-KEY
+to	O
+converge	O
+in	O
+the	O
+worst	B-KEY
+case	I-KEY
+.	O
+∗	O
+This	O
+work	O
+was	O
+supported	O
+by	O
+the	O
+DoD	O
+University	O
+Research	O
+Initiative	O
+-LRB-	O
+URI	O
+-RRB-	O
+administered	O
+by	O
+the	O
+Office	O
+of	O
+Naval	O
+Research	O
+under	O
+Grant	O
+N00014-01-1-0795	O
+.	O
+†	O
+Supported	O
+in	O
+part	O
+by	O
+ONR	O
+grant	O
+N00014-01-0795	O
+and	O
+NSF	O
+grants	O
+CCR-0105337	O
+,	O
+CCR-TC-0208972	O
+,	O
+ANI-0207399	O
+,	O
+and	O
+ITR-0219018	O
+.	O
+‡	O
+This	O
+work	O
+conducted	O
+while	O
+at	O
+NEC	O
+Laboratories	O
+America	O
+,	O
+Princeton	O
+,	O
+NJ	O
+.	O
+
+Nash	O
+Equilibria	O
+in	O
+Graphical	B-KEY
+Games	I-KEY
+on	O
+Trees	O
+Revisited	O
+*	O
+Graphical	B-KEY
+games	I-KEY
+have	O
+been	O
+proposed	O
+as	O
+a	O
+game-theoretic	O
+model	O
+of	O
+large-scale	O
+distributed	O
+networks	O
+of	O
+non-cooperative	O
+agents	O
+.	O
+When	O
+the	O
+number	O
+of	O
+players	O
+is	O
+large	O
+,	O
+and	O
+the	O
+underlying	O
+graph	O
+has	O
+low	O
+degree	B-KEY
+,	O
+they	O
+provide	O
+a	O
+concise	O
+way	O
+to	O
+represent	O
+the	O
+players	O
+'	O
+payoffs	O
+.	O
+It	O
+has	O
+recently	O
+been	O
+shown	O
+that	O
+the	O
+problem	O
+of	O
+finding	O
+Nash	O
+equilibria	O
+in	O
+a	O
+general	O
+degree-3	O
+graphical	B-KEY
+game	I-KEY
+with	O
+two	O
+actions	O
+per	O
+player	O
+is	O
+complete	O
+for	O
+the	O
+complexity	O
+class	O
+PPAD	O
+,	O
+indicating	O
+that	O
+it	O
+is	O
+unlikely	O
+that	O
+there	O
+is	O
+any	O
+polynomial-time	O
+algorithm	O
+for	O
+this	O
+problem	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+study	O
+the	O
+complexity	O
+of	O
+graphical	B-KEY
+games	I-KEY
+with	O
+two	O
+actions	O
+per	O
+player	O
+on	O
+bounded-degree	O
+trees	O
+.	O
+This	O
+setting	O
+was	O
+first	O
+considered	O
+by	O
+Kearns	O
+,	O
+Littman	O
+and	O
+Singh	O
+,	O
+who	O
+proposed	O
+a	O
+dynamic	O
+programming-based	O
+algorithm	O
+that	O
+computes	O
+all	O
+Nash	O
+equilibria	O
+of	O
+such	O
+games	O
+.	O
+The	O
+running	O
+time	O
+of	O
+their	O
+algorithm	O
+is	O
+exponential	O
+,	O
+though	O
+approximate	O
+equilibria	O
+can	O
+be	O
+computed	O
+efficiently	O
+.	O
+Later	O
+,	O
+Littman	O
+,	O
+Kearns	O
+and	O
+Singh	O
+proposed	O
+a	O
+modification	O
+to	O
+this	O
+algorithm	O
+that	O
+can	O
+find	O
+a	O
+single	O
+Nash	B-KEY
+equilibrium	I-KEY
+in	O
+polynomial	O
+time	O
+.	O
+We	O
+show	O
+that	O
+this	O
+modified	O
+algorithm	O
+is	O
+incorrect	O
+--	O
+the	O
+output	O
+is	O
+not	O
+always	O
+a	O
+Nash	B-KEY
+equilibrium	I-KEY
+.	O
+We	O
+then	O
+propose	O
+a	O
+new	O
+algorithm	O
+that	O
+is	O
+based	O
+on	O
+the	O
+ideas	O
+of	O
+Kearns	O
+et	O
+al.	O
+and	O
+computes	O
+all	O
+Nash	O
+equilibria	O
+in	O
+quadratic	O
+time	O
+if	O
+the	O
+input	O
+graph	O
+is	O
+a	O
+path	O
+,	O
+and	O
+in	O
+polynomial	O
+time	O
+if	O
+it	O
+is	O
+an	O
+arbitrary	O
+graph	O
+of	O
+maximum	O
+degree	B-KEY
+2	O
+.	O
+Moreover	O
+,	O
+our	O
+algorithm	O
+can	O
+be	O
+used	O
+to	O
+compute	O
+Nash	O
+equilibria	O
+of	O
+graphical	B-KEY
+games	I-KEY
+on	O
+arbitrary	O
+trees	O
+,	O
+but	O
+the	O
+running	O
+time	O
+can	O
+be	O
+exponential	O
+,	O
+even	O
+when	O
+the	O
+tree	O
+has	O
+bounded	O
+degree	B-KEY
+.	O
+We	O
+show	O
+that	O
+this	O
+is	O
+inevitable	O
+--	O
+any	O
+algorithm	O
+of	O
+this	O
+type	O
+will	O
+take	O
+exponential	O
+time	O
+,	O
+even	O
+on	O
+bounded-degree	O
+trees	O
+with	O
+pathwidth	O
+2	O
+.	O
+It	O
+is	O
+an	O
+open	O
+question	O
+whether	O
+our	O
+algorithm	O
+runs	O
+in	O
+polynomial	O
+time	O
+on	O
+graphs	O
+with	O
+pathwidth	O
+1	O
+,	O
+but	O
+we	O
+show	O
+that	O
+finding	O
+a	O
+Nash	B-KEY
+equilibrium	I-KEY
+for	O
+a	O
+2-action	O
+graphical	B-KEY
+game	I-KEY
+in	O
+which	O
+the	O
+underlying	O
+graph	O
+has	O
+maximum	O
+degree	B-KEY
+3	O
+and	O
+constant	O
+pathwidth	O
+is	O
+PPAD-complete	B-KEY
+-LRB-	O
+so	O
+is	O
+unlikely	O
+to	O
+be	O
+tractable	O
+-RRB-	O
+.	O
+*	O
+This	O
+research	O
+is	O
+supported	O
+by	O
+the	O
+EPSRC	O
+research	O
+grants	O
+``	O
+Algorithmics	O
+of	O
+Network-sharing	O
+Games	O
+''	O
+and	O
+``	O
+Discontinuous	O
+Behaviour	O
+in	O
+the	O
+Complexity	O
+of	O
+randomized	O
+Algorithms	O
+''	O
+.	O
+
+Implementation	B-KEY
+with	O
+a	O
+Bounded	B-KEY
+Action	I-KEY
+Space	I-KEY
+ABSTRACT	O
+While	O
+traditional	O
+mechanism	O
+design	O
+typically	O
+assumes	O
+isomorphism	O
+between	O
+the	O
+agents	O
+'	O
+type	O
+-	O
+and	O
+action	O
+spaces	O
+,	O
+in	O
+many	O
+situations	O
+the	O
+agents	O
+face	O
+strict	O
+restrictions	O
+on	O
+their	O
+action	O
+space	O
+due	O
+to	O
+,	O
+e.g.	O
+,	O
+technical	O
+,	O
+behavioral	O
+or	O
+regulatory	O
+reasons	O
+.	O
+We	O
+devise	O
+a	O
+general	O
+framework	O
+for	O
+the	O
+study	O
+of	O
+mechanism	O
+design	O
+in	O
+single-parameter	O
+environments	O
+with	O
+restricted	O
+action	O
+spaces	O
+.	O
+Our	O
+contribution	O
+is	O
+threefold	O
+.	O
+First	O
+,	O
+we	O
+characterize	O
+sufficient	O
+conditions	O
+under	O
+which	O
+the	O
+information-theoretically	O
+optimal	O
+social-choice	O
+rule	O
+can	O
+be	O
+implemented	B-KEY
+in	O
+dominant	B-KEY
+strategies	I-KEY
+,	O
+and	O
+prove	O
+that	O
+any	O
+multilinear	O
+social-choice	O
+rule	O
+is	O
+dominant-strategy	O
+implementable	B-KEY
+with	O
+no	O
+additional	O
+cost	O
+.	O
+Second	O
+,	O
+we	O
+identify	O
+necessary	O
+conditions	O
+for	O
+the	O
+optimality	O
+of	O
+action-bounded	B-KEY
+mechanisms	I-KEY
+,	O
+and	O
+fully	O
+characterize	O
+the	O
+optimal	B-KEY
+mechanisms	I-KEY
+and	O
+strategies	O
+in	O
+games	O
+with	O
+two	O
+players	O
+and	O
+two	O
+alternatives	O
+.	O
+Finally	O
+,	O
+we	O
+prove	O
+that	O
+for	O
+any	O
+multilinear	O
+social-choice	O
+rule	O
+,	O
+the	O
+optimal	B-KEY
+mechanism	I-KEY
+with	O
+k	O
+actions	O
+incurs	O
+an	O
+expected	O
+loss	O
+of	O
+O	O
+-LRB-	O
+k21	O
+-RRB-	O
+compared	O
+to	O
+the	O
+optimal	B-KEY
+mechanisms	I-KEY
+with	O
+unrestricted	O
+action	O
+spaces	O
+.	O
+Our	O
+results	O
+apply	O
+to	O
+various	O
+economic	O
+and	O
+computational	O
+settings	O
+,	O
+and	O
+we	O
+demonstrate	O
+their	O
+applicability	O
+to	O
+signaling	O
+games	O
+,	O
+public-good	O
+models	O
+and	O
+routing	O
+in	O
+networks	O
+.	O
+
+Sequential	O
+Decision	B-KEY
+Making	O
+in	O
+Parallel	O
+Two-Sided	O
+Economic	O
+Search	O
+ABSTRACT	O
+This	O
+paper	O
+presents	O
+a	O
+two-sided	O
+economic	O
+search	O
+model	O
+in	O
+which	O
+agents	O
+are	O
+searching	O
+for	O
+beneficial	O
+pairwise	B-KEY
+partnerships	I-KEY
+.	O
+In	O
+each	O
+search	O
+stage	O
+,	O
+each	O
+of	O
+the	O
+agents	O
+is	O
+randomly	O
+matched	B-KEY
+with	O
+several	O
+other	O
+agents	O
+in	O
+parallel	O
+,	O
+and	O
+makes	O
+a	O
+decision	B-KEY
+whether	O
+to	O
+accept	O
+a	O
+potential	O
+partnership	B-KEY
+with	O
+one	O
+of	O
+them	O
+.	O
+The	O
+distinguishing	O
+feature	O
+of	O
+the	O
+proposed	O
+model	O
+is	O
+that	O
+the	O
+agents	O
+are	O
+not	O
+restricted	O
+to	O
+maintaining	O
+a	O
+synchronized	O
+-LRB-	O
+instantaneous	O
+-RRB-	O
+decision	B-KEY
+protocol	O
+and	O
+can	O
+sequentially	O
+accept	O
+and	O
+reject	O
+partnerships	B-KEY
+within	O
+the	O
+same	O
+search	O
+stage	O
+.	O
+We	O
+analyze	O
+the	O
+dynamics	O
+which	O
+drive	O
+the	O
+agents	O
+'	O
+strategies	O
+towards	O
+a	O
+stable	O
+equilibrium	O
+in	O
+the	O
+new	O
+model	O
+and	O
+show	O
+that	O
+the	O
+proposed	O
+search	O
+strategy	O
+weakly	O
+dominates	O
+the	O
+one	O
+currently	O
+in	O
+use	O
+for	O
+the	O
+two-sided	O
+parallel	O
+economic	O
+search	O
+model	O
+.	O
+By	O
+identifying	O
+several	O
+unique	O
+characteristics	O
+of	O
+the	O
+equilibrium	O
+we	O
+manage	O
+to	O
+efficiently	O
+bound	O
+the	O
+strategy	O
+space	O
+that	O
+needs	O
+to	O
+be	O
+explored	O
+by	O
+the	O
+agents	O
+and	O
+propose	O
+an	O
+efficient	O
+means	O
+for	O
+extracting	O
+the	O
+distributed	O
+equilibrium	B-KEY
+strategies	I-KEY
+in	O
+common	O
+environments	O
+.	O
+
+SMILE	O
+:	O
+Sound	O
+Multi-agent	O
+Incremental	B-KEY
+LEarning	I-KEY
+;--RRB-	O
+*	O
+ABSTRACT	O
+This	O
+article	O
+deals	O
+with	O
+the	O
+problem	O
+of	O
+collaborative	O
+learning	O
+in	O
+a	O
+multi-agent	O
+system	O
+.	O
+Here	O
+each	O
+agent	B-KEY
+can	O
+update	O
+incrementally	O
+its	O
+beliefs	O
+B	O
+-LRB-	O
+the	O
+concept	O
+representation	O
+-RRB-	O
+so	O
+that	O
+it	O
+is	O
+in	O
+a	O
+way	O
+kept	O
+consistent	O
+with	O
+the	O
+whole	O
+set	O
+of	O
+information	O
+K	O
+-LRB-	O
+the	O
+examples	O
+-RRB-	O
+that	O
+he	O
+has	O
+received	O
+from	O
+the	O
+environment	O
+or	O
+other	O
+agents	B-KEY
+.	O
+We	O
+extend	O
+this	O
+notion	O
+of	O
+consistency	O
+-LRB-	O
+or	O
+soundness	O
+-RRB-	O
+to	O
+the	O
+whole	O
+MAS	O
+and	O
+discuss	O
+how	O
+to	O
+obtain	O
+that	O
+,	O
+at	O
+any	O
+moment	O
+,	O
+a	O
+same	O
+consistent	O
+concept	O
+representation	O
+is	O
+present	O
+in	O
+each	O
+agent	B-KEY
+.	O
+The	O
+corresponding	O
+protocol	O
+is	O
+applied	O
+to	O
+supervised	O
+concept	O
+learning	O
+.	O
+The	O
+resulting	O
+method	O
+SMILE	O
+-LRB-	O
+standing	O
+for	O
+Sound	O
+Multiagent	O
+Incremental	B-KEY
+LEarning	I-KEY
+-RRB-	O
+is	O
+described	O
+and	O
+experimented	O
+here	O
+.	O
+Surprisingly	O
+some	O
+difficult	O
+boolean	O
+formulas	O
+are	O
+better	O
+learned	O
+,	O
+given	O
+the	O
+same	O
+learning	O
+set	O
+,	O
+by	O
+a	O
+Multi	O
+agent	B-KEY
+system	O
+than	O
+by	O
+a	O
+single	O
+agent	B-KEY
+.	O
+
+PackageBLAST	B-KEY
+:	O
+An	O
+Adaptive	B-KEY
+Multi-Policy	I-KEY
+Grid	I-KEY
+Service	I-KEY
+for	O
+Biological	B-KEY
+Sequence	I-KEY
+Comparison	I-KEY
+*	O
+ABSTRACT	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+propose	O
+an	O
+adaptive	O
+task	B-KEY
+allocation	I-KEY
+framework	O
+to	O
+perform	O
+BLAST	B-KEY
+searches	I-KEY
+in	O
+a	O
+grid	B-KEY
+environment	I-KEY
+against	O
+sequence	O
+database	O
+segments	O
+.	O
+The	O
+framework	O
+,	O
+called	O
+PackageBLAST	B-KEY
+,	O
+provides	O
+an	O
+infrastructure	O
+to	O
+choose	O
+or	O
+incorporate	O
+task	B-KEY
+allocation	I-KEY
+strategies	O
+.	O
+Furthermore	O
+,	O
+we	O
+propose	O
+a	O
+mechanism	O
+to	O
+compute	O
+grid	O
+nodes	O
+execution	O
+weight	O
+,	O
+adapting	O
+the	O
+chosen	O
+allocation	O
+policy	O
+to	O
+the	O
+current	O
+computational	O
+power	O
+of	O
+the	O
+nodes	O
+.	O
+Our	O
+results	O
+present	O
+very	O
+good	O
+speedups	O
+and	O
+also	O
+show	O
+that	O
+no	O
+single	O
+allocation	O
+strategy	O
+is	O
+able	O
+to	O
+achieve	O
+the	O
+lowest	O
+execution	O
+times	O
+for	O
+all	O
+scenarios	O
+.	O
+
+Analyzing	O
+Feature	O
+Trajectories	O
+for	O
+Event	B-KEY
+Detection	I-KEY
+ABSTRACT	O
+We	O
+consider	O
+the	O
+problem	O
+of	O
+analyzing	O
+word	B-KEY
+trajectories	I-KEY
+in	O
+both	O
+time	O
+and	O
+frequency	O
+domains	O
+,	O
+with	O
+the	O
+specific	O
+goal	O
+of	O
+identifying	O
+important	O
+and	O
+less-reported	O
+,	O
+periodic	O
+and	O
+aperiodic	O
+words	O
+.	O
+A	O
+set	O
+of	O
+words	O
+with	O
+identical	O
+trends	O
+can	O
+be	O
+grouped	O
+together	O
+to	O
+reconstruct	O
+an	O
+event	O
+in	O
+a	O
+completely	O
+unsupervised	O
+manner	O
+.	O
+The	O
+document	O
+frequency	O
+of	O
+each	O
+word	O
+across	O
+time	O
+is	O
+treated	O
+like	O
+a	O
+time	B-KEY
+series	I-KEY
+,	O
+where	O
+each	O
+element	O
+is	O
+the	O
+document	O
+frequency	O
+-	O
+inverse	O
+document	O
+frequency	O
+-LRB-	O
+DFIDF	O
+-RRB-	O
+score	O
+at	O
+one	O
+time	O
+point	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+1	O
+-RRB-	O
+first	O
+applied	O
+spectral	B-KEY
+analysis	I-KEY
+to	O
+categorize	O
+features	O
+for	O
+different	O
+event	O
+characteristics	O
+:	O
+important	O
+and	O
+less-reported	O
+,	O
+periodic	O
+and	O
+aperiodic	O
+;	O
+2	O
+-RRB-	O
+modeled	O
+aperiodic	O
+features	O
+with	O
+Gaussian	B-KEY
+density	O
+and	O
+periodic	O
+features	O
+with	O
+Gaussian	B-KEY
+mixture	O
+densities	O
+,	O
+and	O
+subsequently	O
+detected	O
+each	O
+feature	O
+'s	O
+burst	O
+by	O
+the	O
+truncated	O
+Gaussian	B-KEY
+approach	O
+;	O
+3	O
+-RRB-	O
+proposed	O
+an	O
+unsupervised	O
+greedy	O
+event	B-KEY
+detection	I-KEY
+algorithm	O
+to	O
+detect	O
+both	O
+aperiodic	O
+and	O
+periodic	B-KEY
+events	I-KEY
+.	O
+All	O
+of	O
+the	O
+above	O
+methods	O
+can	O
+be	O
+applied	O
+to	O
+time	B-KEY
+series	I-KEY
+data	O
+in	O
+general	O
+.	O
+We	O
+extensively	O
+evaluated	O
+our	O
+methods	O
+on	O
+the	O
+1-year	O
+Reuters	O
+News	O
+Corpus	O
+-LSB-	O
+3	O
+-RSB-	O
+and	O
+showed	O
+that	O
+they	O
+were	O
+able	O
+to	O
+uncover	O
+meaningful	O
+aperiodic	O
+and	O
+periodic	B-KEY
+events	I-KEY
+.	O
+
+Studying	O
+the	O
+Use	O
+of	O
+Popular	B-KEY
+Destinations	I-KEY
+to	O
+Enhance	B-KEY
+Web	I-KEY
+Search	I-KEY
+Interaction	O
+ABSTRACT	O
+We	O
+present	O
+a	O
+novel	O
+Web	B-KEY
+search	I-KEY
+interaction	I-KEY
+feature	O
+which	O
+,	O
+for	O
+a	O
+given	O
+query	O
+,	O
+provides	O
+links	O
+to	O
+websites	O
+frequently	O
+visited	O
+by	O
+other	O
+users	O
+with	O
+similar	O
+information	O
+needs	O
+.	O
+These	O
+popular	B-KEY
+destinations	I-KEY
+complement	O
+traditional	O
+search	O
+results	O
+,	O
+allowing	O
+direct	O
+navigation	O
+to	O
+authoritative	O
+resources	O
+for	O
+the	O
+query	O
+topic	O
+.	O
+Destinations	O
+are	O
+identified	O
+using	O
+the	O
+history	O
+of	O
+search	O
+and	O
+browsing	O
+behavior	O
+of	O
+many	O
+users	O
+over	O
+an	O
+extended	O
+time	O
+period	O
+,	O
+whose	O
+collective	O
+behavior	O
+provides	O
+a	O
+basis	O
+for	O
+computing	O
+source	O
+authority	O
+.	O
+We	O
+describe	O
+a	O
+user	B-KEY
+study	I-KEY
+which	O
+compared	O
+the	O
+suggestion	O
+of	O
+destinations	O
+with	O
+the	O
+previously	O
+proposed	O
+suggestion	O
+of	O
+related	B-KEY
+queries	I-KEY
+,	O
+as	O
+well	O
+as	O
+with	O
+traditional	O
+,	O
+unaided	O
+Web	O
+search	O
+.	O
+Results	O
+show	O
+that	O
+search	O
+enhanced	O
+by	O
+destination	O
+suggestions	O
+outperforms	O
+other	O
+systems	O
+for	O
+exploratory	O
+tasks	O
+,	O
+with	O
+best	O
+performance	O
+obtained	O
+from	O
+mining	O
+past	O
+user	O
+behavior	O
+at	O
+query-level	O
+granularity	O
+.	O
+
+Scalable	O
+Grid	B-KEY
+Service	I-KEY
+Discovery	I-KEY
+Based	O
+on	O
+UDDI	O
+*	O
+ABSTRACT	O
+Efficient	O
+discovery	B-KEY
+of	O
+grid	O
+services	O
+is	O
+essential	O
+for	O
+the	O
+success	O
+of	O
+grid	B-KEY
+computing	I-KEY
+.	O
+The	O
+standardization	O
+of	O
+grids	O
+based	O
+on	O
+web	B-KEY
+services	I-KEY
+has	O
+resulted	O
+in	O
+the	O
+need	O
+for	O
+scalable	O
+web	B-KEY
+service	I-KEY
+discovery	B-KEY
+mechanisms	O
+to	O
+be	O
+deployed	O
+in	O
+grids	O
+Even	O
+though	O
+UDDI	B-KEY
+has	O
+been	O
+the	O
+de	O
+facto	O
+industry	O
+standard	O
+for	O
+web-services	O
+discovery	B-KEY
+,	O
+imposed	O
+requirements	O
+of	O
+tight-replication	O
+among	O
+registries	O
+and	O
+lack	O
+of	O
+autonomous	B-KEY
+control	I-KEY
+has	O
+severely	O
+hindered	O
+its	O
+widespread	O
+deployment	O
+and	O
+usage	O
+.	O
+With	O
+the	O
+advent	O
+of	O
+grid	B-KEY
+computing	I-KEY
+the	O
+scalability	B-KEY
+issue	I-KEY
+of	O
+UDDI	B-KEY
+will	O
+become	O
+a	O
+roadblock	O
+that	O
+will	O
+prevent	O
+its	O
+deployment	O
+in	O
+grids	O
+.	O
+In	O
+this	O
+paper	O
+we	O
+present	O
+our	O
+distributed	O
+web-service	O
+discovery	B-KEY
+architecture	O
+,	O
+called	O
+DUDE	O
+-LRB-	O
+Distributed	O
+UDDI	O
+Deployment	O
+Engine	O
+-RRB-	O
+.	O
+DUDE	O
+leverages	O
+DHT	B-KEY
+-LRB-	O
+Distributed	O
+Hash	O
+Tables	O
+-RRB-	O
+as	O
+a	O
+rendezvous	O
+mechanism	O
+between	O
+multiple	O
+UDDI	B-KEY
+registries	O
+.	O
+DUDE	O
+enables	O
+consumers	O
+to	O
+query	B-KEY
+multiple	O
+registries	O
+,	O
+still	O
+at	O
+the	O
+same	O
+time	O
+allowing	O
+organizations	O
+to	O
+have	O
+autonomous	B-KEY
+control	I-KEY
+over	O
+their	O
+registries	O
+.	O
+.	O
+Based	O
+on	O
+preliminary	O
+prototype	O
+on	O
+PlanetLab	O
+,	O
+we	O
+believe	O
+that	O
+DUDE	O
+architecture	O
+can	O
+support	O
+effective	O
+distribution	O
+of	O
+UDDI	B-KEY
+registries	O
+thereby	O
+making	O
+UDDI	O
+more	O
+robust	O
+and	O
+also	O
+addressing	O
+its	O
+scaling	O
+issues	O
+.	O
+Furthermore	O
+,	O
+The	O
+DUDE	O
+architecture	O
+for	O
+scalable	O
+distribution	O
+can	O
+be	O
+applied	O
+beyond	O
+UDDI	B-KEY
+to	O
+any	O
+Grid	B-KEY
+Service	I-KEY
+Discovery	I-KEY
+mechanism	O
+.	O
+
+An	O
+Adversarial	B-KEY
+Environment	I-KEY
+Model	O
+for	O
+Bounded	O
+Rational	O
+Agents	B-KEY
+in	O
+Zero-Sum	O
+Interactions	B-KEY
+ABSTRACT	O
+Multiagent	B-KEY
+environments	I-KEY
+are	O
+often	O
+not	O
+cooperative	O
+nor	O
+collaborative	O
+;	O
+in	O
+many	O
+cases	O
+,	O
+agents	B-KEY
+have	O
+conflicting	O
+interests	O
+,	O
+leading	O
+to	O
+adversarial	B-KEY
+interactions	I-KEY
+.	O
+This	O
+paper	O
+presents	O
+a	O
+formal	O
+Adversarial	B-KEY
+Environment	I-KEY
+model	O
+for	O
+bounded	O
+rational	O
+agents	B-KEY
+operating	O
+in	O
+a	O
+zero-sum	O
+environment	O
+.	O
+In	O
+such	O
+environments	O
+,	O
+attempts	O
+to	O
+use	O
+classical	O
+utility-based	O
+search	O
+methods	O
+can	O
+raise	O
+a	O
+variety	O
+of	O
+difficulties	O
+-LRB-	O
+e.g.	O
+,	O
+implicitly	O
+modeling	O
+the	O
+opponent	O
+as	O
+an	O
+omniscient	O
+utility	O
+maximizer	O
+,	O
+rather	O
+than	O
+leveraging	O
+a	O
+more	O
+nuanced	O
+,	O
+explicit	O
+opponent	O
+model	O
+-RRB-	O
+.	O
+We	O
+define	O
+an	O
+Adversarial	B-KEY
+Environment	I-KEY
+by	O
+describing	O
+the	O
+mental	O
+states	O
+of	O
+an	O
+agent	B-KEY
+in	O
+such	O
+an	O
+environment	O
+.	O
+We	O
+then	O
+present	O
+behavioral	B-KEY
+axioms	I-KEY
+that	O
+are	O
+intended	O
+to	O
+serve	O
+as	O
+design	O
+principles	O
+for	O
+building	O
+such	O
+adversarial	O
+agents	B-KEY
+.	O
+We	O
+explore	O
+the	O
+application	O
+of	O
+our	O
+approach	O
+by	O
+analyzing	O
+log	O
+files	O
+of	O
+completed	O
+Connect-Four	B-KEY
+games	I-KEY
+,	O
+and	O
+present	O
+an	O
+empirical	O
+analysis	O
+of	O
+the	O
+axioms	O
+'	O
+appropriateness	O
+.	O
+
+Worst-Case	O
+Optimal	O
+Redistribution	O
+of	O
+VCG	O
+Payments	O
+in	O
+Heterogeneous-Item	O
+Auctions	O
+with	O
+Unit	O
+Demand	O
+ABSTRACT	O
+Many	O
+important	O
+problems	O
+in	O
+multiagent	O
+systems	O
+involve	O
+the	O
+allocation	O
+of	O
+multiple	O
+resources	O
+among	O
+the	O
+agents	O
+.	O
+For	O
+resource	O
+allocation	O
+problems	O
+,	O
+the	O
+well-known	O
+VCG	O
+mechanism	B-KEY
+satisfies	O
+a	O
+list	O
+of	O
+desired	O
+properties	O
+,	O
+including	O
+efficiency	O
+,	O
+strategy-proofness	O
+,	O
+individual	O
+rationality	O
+,	O
+and	O
+the	O
+non-deficit	O
+property	O
+.	O
+However	O
+,	O
+VCG	O
+is	O
+generally	O
+not	O
+budget-balanced	O
+.	O
+Under	O
+VCG	O
+,	O
+agents	O
+pay	O
+the	O
+VCG	O
+payments	O
+,	O
+which	O
+reduces	O
+social	O
+welfare	O
+.	O
+To	O
+offset	O
+the	O
+loss	O
+of	O
+social	O
+welfare	O
+due	O
+to	O
+the	O
+VCG	O
+payments	O
+,	O
+VCG	O
+redistribution	O
+mechanisms	B-KEY
+were	O
+introduced	O
+.	O
+These	O
+mechanisms	B-KEY
+aim	O
+to	O
+redistribute	O
+as	O
+much	O
+VCG	O
+payments	O
+back	O
+to	O
+the	O
+agents	O
+as	O
+possible	O
+,	O
+while	O
+maintaining	O
+the	O
+aforementioned	O
+desired	O
+properties	O
+of	O
+the	O
+VCG	O
+mechanism	B-KEY
+.	O
+We	O
+continue	O
+the	O
+search	O
+for	O
+worst-case	O
+optimal	O
+VCG	O
+redistribution	O
+mechanisms	B-KEY
+--	O
+mechanisms	B-KEY
+that	O
+maximize	O
+the	O
+fraction	O
+of	O
+total	O
+VCG	O
+payment	B-KEY
+redistributed	I-KEY
+in	O
+the	O
+worst	O
+case	O
+.	O
+Previously	O
+,	O
+a	O
+worst-case	O
+optimal	O
+VCG	O
+redistribution	O
+mechanism	B-KEY
+-LRB-	O
+denoted	O
+by	O
+WCO	O
+-RRB-	O
+was	O
+characterized	O
+for	O
+multi-unit	O
+auctions	O
+with	O
+nonincreasing	O
+marginal	O
+values	O
+-LSB-	O
+7	O
+-RSB-	O
+.	O
+Later	O
+,	O
+WCO	O
+was	O
+generalized	O
+to	O
+settings	O
+involving	O
+heterogeneous	O
+items	O
+-LSB-	O
+4	O
+-RSB-	O
+,	O
+resulting	O
+in	O
+the	O
+HETERO	O
+mechanism	B-KEY
+.	O
+-LSB-	O
+4	O
+-RSB-	O
+conjectured	O
+that	O
+HETERO	O
+is	O
+feasible	O
+and	O
+worst-case	O
+optimal	O
+for	O
+heterogeneous-item	O
+auctions	O
+with	O
+unit	O
+demand	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+propose	O
+a	O
+more	O
+natural	O
+way	O
+to	O
+generalize	O
+the	O
+WCO	O
+mechanism	B-KEY
+.	O
+We	O
+prove	O
+that	O
+our	O
+generalized	O
+mechanism	B-KEY
+,	O
+though	O
+represented	O
+differently	O
+,	O
+actually	O
+coincides	O
+with	O
+HETERO	O
+.	O
+Based	O
+on	O
+this	O
+new	O
+representation	O
+of	O
+HETERO	O
+,	O
+we	O
+prove	O
+that	O
+HETERO	O
+is	O
+indeed	O
+feasible	O
+and	O
+worst-case	O
+optimal	O
+in	O
+heterogeneous-item	O
+auctions	O
+with	O
+unit	O
+demand	O
+.	O
+Finally	O
+,	O
+we	O
+conjecture	O
+that	O
+HETERO	O
+remains	O
+feasible	O
+and	O
+worst-case	O
+optimal	O
+in	O
+the	O
+even	O
+more	O
+general	O
+setting	O
+of	O
+combinatorial	O
+auctions	O
+with	O
+gross	O
+substitutes	O
+.	O
+
+Rewards-Based	O
+Negotiation	B-KEY
+for	O
+Providing	O
+Context	O
+Information	O
+ABSTRACT	O
+How	O
+to	O
+provide	O
+appropriate	O
+context	O
+information	O
+is	O
+a	O
+challenging	O
+problem	O
+in	O
+context-aware	B-KEY
+computing	O
+.	O
+Most	O
+existing	O
+approaches	O
+use	O
+a	O
+centralized	O
+selection	O
+mechanism	O
+to	O
+decide	O
+which	O
+context	O
+information	O
+is	O
+appropriate	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+propose	O
+a	O
+novel	O
+approach	O
+based	O
+on	O
+negotiation	B-KEY
+with	O
+rewards	O
+to	O
+solving	O
+such	O
+problem	O
+.	O
+Distributed	O
+context	B-KEY
+providers	I-KEY
+negotiate	B-KEY
+with	O
+each	O
+other	O
+to	O
+decide	O
+who	O
+can	O
+provide	O
+context	O
+and	O
+how	O
+they	O
+allocate	O
+proceeds	O
+.	O
+In	O
+order	O
+to	O
+support	O
+our	O
+approach	O
+,	O
+we	O
+have	O
+designed	O
+a	O
+concrete	O
+negotiation	B-KEY
+model	O
+with	O
+rewards	O
+.	O
+We	O
+also	O
+evaluate	O
+our	O
+approach	O
+and	O
+show	O
+that	O
+it	O
+indeed	O
+can	O
+choose	O
+an	O
+appropriate	O
+context	B-KEY
+provider	I-KEY
+and	O
+allocate	O
+the	O
+proceeds	O
+fairly	O
+.	O
+
+Topic	B-KEY
+Segmentation	I-KEY
+with	O
+Shared	B-KEY
+Topic	I-KEY
+Detection	O
+and	O
+Alignment	O
+of	O
+Multiple	O
+Documents	O
+ABSTRACT	O
+Topic	B-KEY
+detection	I-KEY
+and	O
+tracking	B-KEY
+-LSB-	O
+26	O
+-RSB-	O
+and	O
+topic	B-KEY
+segmentation	I-KEY
+-LSB-	O
+15	O
+-RSB-	O
+play	O
+an	O
+important	O
+role	O
+in	O
+capturing	O
+the	O
+local	B-KEY
+and	I-KEY
+sequential	I-KEY
+information	I-KEY
+of	I-KEY
+documents	I-KEY
+.	O
+Previous	O
+work	O
+in	O
+this	O
+area	O
+usually	O
+focuses	O
+on	O
+single	B-KEY
+documents	I-KEY
+,	O
+although	O
+similar	O
+multiple	B-KEY
+documents	I-KEY
+are	O
+available	O
+in	O
+many	O
+domains	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+introduce	O
+a	O
+novel	O
+unsupervised	O
+method	O
+for	O
+shared	B-KEY
+topic	I-KEY
+detection	O
+and	O
+topic	O
+segmentation	O
+of	O
+multiple	O
+similar	O
+documents	O
+based	O
+on	O
+mutual	O
+information	O
+-LRB-	O
+MI	O
+-RRB-	O
+and	O
+weighted	O
+mutual	O
+information	O
+-LRB-	O
+WMI	O
+-RRB-	O
+that	O
+is	O
+a	O
+combination	O
+of	O
+MI	O
+and	O
+term	O
+weights	O
+.	O
+The	O
+basic	O
+idea	O
+is	O
+that	O
+the	O
+optimal	O
+segmentation	O
+maximizes	O
+MI	O
+-LRB-	O
+or	O
+WMI	O
+-RRB-	O
+.	O
+Our	O
+approach	O
+can	O
+detect	O
+shared	B-KEY
+topics	I-KEY
+among	O
+documents	O
+.	O
+It	O
+can	O
+find	O
+the	O
+optimal	B-KEY
+boundaries	I-KEY
+in	O
+a	O
+document	O
+,	O
+and	O
+align	O
+segments	O
+among	O
+documents	O
+at	O
+the	O
+same	O
+time	O
+.	O
+It	O
+also	O
+can	O
+handle	O
+single-document	O
+segmentation	O
+as	O
+a	O
+special	O
+case	O
+of	O
+the	O
+multi-document	O
+segmentation	O
+and	O
+alignment	O
+.	O
+Our	O
+methods	O
+can	O
+identify	O
+and	O
+strengthen	O
+cue	B-KEY
+terms	I-KEY
+that	O
+can	O
+be	O
+used	O
+for	O
+segmentation	O
+and	O
+partially	O
+remove	O
+stop	B-KEY
+words	I-KEY
+by	O
+using	O
+term	B-KEY
+weights	I-KEY
+based	O
+on	O
+entropy	O
+learned	O
+from	O
+multiple	B-KEY
+documents	I-KEY
+.	O
+Our	O
+experimental	O
+results	O
+show	O
+that	O
+our	O
+algorithm	O
+works	O
+well	O
+for	O
+the	O
+tasks	O
+of	O
+single-document	O
+segmentation	O
+,	O
+shared	B-KEY
+topic	I-KEY
+detection	O
+,	O
+and	O
+multi-document	O
+segmentation	O
+.	O
+Utilizing	O
+information	O
+from	O
+multiple	B-KEY
+documents	I-KEY
+can	O
+tremendously	O
+improve	O
+the	O
+performance	B-KEY
+of	I-KEY
+topic	I-KEY
+segmentation	I-KEY
+,	O
+and	O
+using	O
+WMI	O
+is	O
+even	O
+better	O
+than	O
+using	O
+MI	O
+for	O
+the	O
+multi-document	O
+segmentation	O
+.	O
+
+EDAS	B-KEY
+:	O
+Providing	O
+an	O
+Environment	O
+for	O
+Decentralized	O
+Adaptive	B-KEY
+Services	O
+ABSTRACT	O
+As	O
+the	O
+idea	O
+of	O
+virtualisation	O
+of	O
+compute	O
+power	O
+,	O
+storage	O
+and	O
+bandwidth	O
+becomes	O
+more	O
+and	O
+more	O
+important	O
+,	O
+grid	B-KEY
+computing	I-KEY
+evolves	O
+and	O
+is	O
+applied	O
+to	O
+a	O
+rising	O
+number	O
+of	O
+applications	O
+.	O
+The	O
+environment	O
+for	O
+decentralized	O
+adaptive	B-KEY
+services	O
+-LRB-	O
+EDAS	O
+-RRB-	O
+provides	O
+a	O
+grid-like	O
+infrastructure	O
+for	O
+user-accessed	O
+,	O
+longterm	O
+services	O
+-LRB-	O
+e.g.	O
+webserver	O
+,	O
+source-code	O
+repository	O
+etc.	O
+-RRB-	O
+.	O
+It	O
+aims	O
+at	O
+supporting	O
+the	O
+autonomous	O
+execution	O
+and	O
+evolution	O
+of	O
+services	O
+in	O
+terms	O
+of	O
+scalability	O
+and	O
+resource-aware	O
+distribution	O
+.	O
+EDAS	B-KEY
+offers	O
+flexible	O
+service	O
+models	O
+based	O
+on	O
+distributed	O
+mobile	O
+objects	O
+ranging	O
+from	O
+a	O
+traditional	O
+clientserver	O
+scenario	O
+to	O
+a	O
+fully	O
+peer-to-peer	O
+based	O
+approach	O
+.	O
+Automatic	O
+,	O
+dynamic	O
+resource	B-KEY
+management	O
+allows	O
+optimized	O
+use	O
+of	O
+available	O
+resources	O
+while	O
+minimizing	O
+the	O
+administrative	O
+complexity	O
+.	O
+
+Distributed	O
+Task	B-KEY
+Allocation	I-KEY
+in	O
+Social	O
+Networks	O
+ABSTRACT	O
+This	O
+paper	O
+proposes	O
+a	O
+new	O
+variant	O
+of	O
+the	O
+task	B-KEY
+allocation	I-KEY
+problem	O
+,	O
+where	O
+the	O
+agents	O
+are	O
+connected	O
+in	O
+a	O
+social	O
+network	O
+and	O
+tasks	O
+arrive	O
+at	O
+the	O
+agents	O
+distributed	O
+over	O
+the	O
+network	O
+.	O
+We	O
+show	O
+that	O
+the	O
+complexity	O
+of	O
+this	O
+problem	O
+remains	O
+NPhard	O
+.	O
+Moreover	O
+,	O
+it	O
+is	O
+not	O
+approximable	O
+within	O
+some	O
+factor	O
+.	O
+We	O
+develop	O
+an	O
+algorithm	B-KEY
+based	O
+on	O
+the	O
+contract-net	O
+protocol	O
+.	O
+Our	O
+algorithm	B-KEY
+is	O
+completely	O
+distributed	O
+,	O
+and	O
+it	O
+assumes	O
+that	O
+agents	B-KEY
+have	O
+only	O
+local	O
+knowledge	O
+about	O
+tasks	O
+and	O
+resources	B-KEY
+.	O
+We	O
+conduct	O
+a	O
+set	O
+of	O
+experiments	O
+to	O
+evaluate	O
+the	O
+performance	O
+and	O
+scalability	O
+of	O
+the	O
+proposed	O
+algorithm	B-KEY
+in	O
+terms	O
+of	O
+solution	O
+quality	O
+and	O
+computation	O
+time	O
+.	O
+Three	O
+different	O
+types	O
+of	O
+networks	O
+,	O
+namely	O
+small-world	O
+,	O
+random	O
+and	O
+scale-free	O
+networks	O
+,	O
+are	O
+used	O
+to	O
+represent	O
+various	O
+social	B-KEY
+relationships	I-KEY
+among	O
+agents	B-KEY
+in	O
+realistic	O
+applications	O
+.	O
+The	O
+results	O
+demonstrate	O
+that	O
+our	O
+algorithm	B-KEY
+works	O
+well	O
+and	O
+that	O
+it	O
+scales	O
+well	O
+to	O
+large-scale	O
+applications	O
+.	O
+
+Towards	O
+Task-based	O
+Personal	B-KEY
+Information	I-KEY
+Management	I-KEY
+Evaluations	O
+ABSTRACT	O
+Personal	B-KEY
+Information	I-KEY
+Management	I-KEY
+-LRB-	O
+PIM	O
+-RRB-	O
+is	O
+a	O
+rapidly	O
+growing	O
+area	O
+of	O
+research	O
+concerned	O
+with	O
+how	O
+people	O
+store	O
+,	O
+manage	O
+and	O
+re-find	B-KEY
+information	I-KEY
+.	O
+A	O
+feature	O
+of	O
+PIM	O
+research	O
+is	O
+that	O
+many	O
+systems	O
+have	O
+been	O
+designed	O
+to	O
+assist	O
+users	O
+manage	O
+and	O
+re-find	B-KEY
+information	I-KEY
+,	O
+but	O
+very	O
+few	O
+have	O
+been	O
+evaluated	O
+.	O
+This	O
+has	O
+been	O
+noted	O
+by	O
+several	O
+scholars	O
+and	O
+explained	O
+by	O
+the	O
+difficulties	O
+involved	O
+in	O
+performing	O
+PIM	O
+evaluations	O
+.	O
+The	O
+difficulties	O
+include	O
+that	O
+people	O
+re-find	B-KEY
+information	I-KEY
+from	O
+within	O
+unique	O
+personal	O
+collections	O
+;	O
+researchers	O
+know	O
+little	O
+about	O
+the	O
+tasks	O
+that	O
+cause	O
+people	O
+to	O
+re-find	B-KEY
+information	I-KEY
+;	O
+and	O
+numerous	O
+privacy	B-KEY
+issues	I-KEY
+concerning	O
+personal	O
+information	O
+.	O
+In	O
+this	O
+paper	O
+we	O
+aim	O
+to	O
+facilitate	O
+PIM	O
+evaluations	O
+by	O
+addressing	O
+each	O
+of	O
+these	O
+difficulties	O
+.	O
+In	O
+the	O
+first	O
+part	O
+,	O
+we	O
+present	O
+a	O
+diary	O
+study	O
+of	O
+information	O
+re-finding	O
+tasks	O
+.	O
+The	O
+study	O
+examines	O
+the	O
+kind	O
+of	O
+tasks	O
+that	O
+require	O
+users	O
+to	O
+re-find	B-KEY
+information	I-KEY
+and	O
+produces	O
+a	O
+taxonomy	B-KEY
+of	O
+re-finding	O
+tasks	O
+for	O
+email	B-KEY
+messages	I-KEY
+and	O
+web	O
+pages	O
+.	O
+In	O
+the	O
+second	O
+part	O
+,	O
+we	O
+propose	O
+a	O
+task-based	O
+evaluation	O
+methodology	O
+based	O
+on	O
+our	O
+findings	O
+and	O
+examine	O
+the	O
+feasibility	O
+of	O
+the	O
+approach	O
+using	O
+two	O
+different	O
+methods	O
+of	O
+task	O
+creation	O
+.	O
+
+Distributed	O
+Management	B-KEY
+of	O
+Flexible	B-KEY
+Times	I-KEY
+Schedules	B-KEY
+ABSTRACT	O
+We	O
+consider	O
+the	O
+problem	O
+of	O
+managing	B-KEY
+schedules	O
+in	O
+an	O
+uncertain	O
+,	O
+distributed	O
+environment	O
+.	O
+We	O
+assume	O
+a	O
+team	O
+of	O
+collaborative	O
+agents	O
+,	O
+each	O
+responsible	O
+for	O
+executing	O
+a	O
+portion	O
+of	O
+a	O
+globally	O
+pre-established	O
+schedule	B-KEY
+,	O
+but	O
+none	O
+possessing	O
+a	O
+global	O
+view	O
+of	O
+either	O
+the	O
+problem	O
+or	O
+solution	O
+.	O
+The	O
+goal	O
+is	O
+to	O
+maximize	O
+the	O
+joint	O
+quality	O
+obtained	O
+from	O
+the	O
+activities	O
+executed	O
+by	O
+all	O
+agents	O
+,	O
+given	O
+that	O
+,	O
+during	O
+execution	O
+,	O
+unexpected	O
+events	O
+will	O
+force	O
+changes	O
+to	O
+some	O
+prescribed	O
+activities	O
+and	O
+reduce	O
+the	O
+utility	O
+of	O
+executing	O
+others	O
+.	O
+We	O
+describe	O
+an	O
+agent	B-KEY
+architecture	I-KEY
+for	O
+solving	O
+this	O
+problem	O
+that	O
+couples	O
+two	O
+basic	O
+mechanisms	O
+:	O
+-LRB-	O
+1	O
+-RRB-	O
+a	O
+``	O
+flexible	B-KEY
+times	I-KEY
+''	O
+representation	O
+of	O
+the	O
+agent	O
+'s	O
+schedule	B-KEY
+-LRB-	O
+using	O
+a	O
+Simple	O
+Temporal	O
+Network	O
+-RRB-	O
+and	O
+-LRB-	O
+2	O
+-RRB-	O
+an	O
+incremental	O
+rescheduling	O
+procedure	O
+.	O
+The	O
+former	O
+hedges	O
+against	O
+temporal	O
+uncertainty	O
+by	O
+allowing	O
+execution	O
+to	O
+proceed	O
+from	O
+a	O
+set	O
+of	O
+feasible	O
+solutions	O
+,	O
+and	O
+the	O
+latter	O
+acts	O
+to	O
+revise	O
+the	O
+agent	O
+'s	O
+schedule	B-KEY
+when	O
+execution	O
+is	O
+forced	O
+outside	O
+of	O
+this	O
+set	O
+of	O
+solutions	O
+or	O
+when	O
+execution	O
+events	O
+reduce	O
+the	O
+expected	O
+value	O
+of	O
+this	O
+feasible	O
+solution	O
+set	O
+.	O
+Basic	O
+coordination	O
+with	O
+other	O
+agents	O
+is	O
+achieved	O
+simply	O
+by	O
+communicating	O
+schedule	B-KEY
+changes	O
+to	O
+those	O
+agents	O
+with	O
+inter-dependent	B-KEY
+activities	I-KEY
+.	O
+Then	O
+,	O
+as	O
+time	O
+permits	O
+,	O
+the	O
+core	O
+local	O
+problem	O
+solving	O
+infra-structure	O
+is	O
+used	O
+to	O
+drive	O
+an	O
+inter-agent	O
+option	O
+generation	O
+and	O
+query	O
+process	O
+,	O
+aimed	O
+at	O
+identifying	O
+opportunities	O
+for	O
+solution	O
+improvement	O
+through	O
+joint	O
+change	O
+.	O
+Using	O
+a	O
+simulator	O
+to	O
+model	O
+the	O
+environment	O
+,	O
+we	O
+compare	O
+the	O
+performance	B-KEY
+of	O
+our	O
+multi-agent	O
+system	O
+with	O
+that	O
+of	O
+an	O
+expected	O
+optimal	O
+-LRB-	O
+but	O
+non-scalable	O
+-RRB-	O
+centralized	O
+MDP	O
+solver	O
+.	O
+
+Laplacian	O
+Optimal	O
+Design	O
+for	O
+Imag	O
+e	O
+Retrieval	O
+ABSTRACT	O
+Relevance	B-KEY
+feedback	I-KEY
+is	O
+a	O
+powerful	O
+technique	O
+to	O
+enhance	O
+ContentBased	B-KEY
+Image	I-KEY
+Retrieval	I-KEY
+-LRB-	O
+CBIR	O
+-RRB-	O
+performance	O
+.	O
+It	O
+solicits	O
+the	O
+user	O
+'s	O
+relevance	O
+judgments	O
+on	O
+the	O
+retrieved	O
+images	O
+returned	O
+by	O
+the	O
+CBIR	O
+systems	O
+.	O
+The	O
+user	O
+'s	O
+labeling	B-KEY
+is	O
+then	O
+used	O
+to	O
+learn	O
+a	O
+classifier	O
+to	O
+distinguish	O
+between	O
+relevant	O
+and	O
+irrelevant	O
+images	O
+.	O
+However	O
+,	O
+the	O
+top	B-KEY
+returned	I-KEY
+images	I-KEY
+may	O
+not	O
+be	O
+the	O
+most	O
+informative	O
+ones	O
+.	O
+The	O
+challenge	O
+is	O
+thus	O
+to	O
+determine	O
+which	O
+unlabeled	O
+images	O
+would	O
+be	O
+the	O
+most	O
+informative	O
+-LRB-	O
+i.e.	O
+,	O
+improve	O
+the	O
+classifier	O
+the	O
+most	O
+-RRB-	O
+if	O
+they	O
+were	O
+labeled	B-KEY
+and	O
+used	O
+as	O
+training	O
+samples	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+propose	O
+a	O
+novel	O
+active	B-KEY
+learning	I-KEY
+algorithm	O
+,	O
+called	O
+Laplacian	O
+Optimal	O
+Design	O
+-LRB-	O
+LOD	O
+-RRB-	O
+,	O
+for	O
+relevance	B-KEY
+feedback	I-KEY
+image	B-KEY
+retrieval	I-KEY
+.	O
+Our	O
+algorithm	O
+is	O
+based	O
+on	O
+a	O
+regression	O
+model	O
+which	O
+minimizes	O
+the	O
+least	O
+square	O
+error	O
+on	O
+the	O
+measured	O
+-LRB-	O
+or	O
+,	O
+labeled	B-KEY
+-RRB-	O
+images	O
+and	O
+simultaneously	O
+preserves	O
+the	O
+local	O
+geometrical	O
+structure	O
+of	O
+the	O
+image	O
+space	O
+.	O
+Specifically	O
+,	O
+we	O
+assume	O
+that	O
+if	O
+two	O
+images	O
+are	O
+sufficiently	O
+close	O
+to	O
+each	O
+other	O
+,	O
+then	O
+their	O
+measurements	O
+-LRB-	O
+or	O
+,	O
+labels	B-KEY
+-RRB-	O
+are	O
+close	O
+as	O
+well	O
+.	O
+By	O
+constructing	O
+a	O
+nearest	O
+neighbor	O
+graph	O
+,	O
+the	O
+geometrical	O
+structure	O
+of	O
+the	O
+image	O
+space	O
+can	O
+be	O
+described	O
+by	O
+the	O
+graph	O
+Laplacian	O
+.	O
+We	O
+discuss	O
+how	O
+results	O
+from	O
+the	O
+field	O
+of	O
+optimal	B-KEY
+experimental	I-KEY
+design	I-KEY
+may	O
+be	O
+used	O
+to	O
+guide	O
+our	O
+selection	O
+of	O
+a	O
+subset	O
+of	O
+images	O
+,	O
+which	O
+gives	O
+us	O
+the	O
+most	O
+amount	O
+of	O
+information	O
+.	O
+Experimental	O
+results	O
+on	O
+Corel	O
+database	O
+suggest	O
+that	O
+the	O
+proposed	O
+approach	O
+achieves	O
+higher	O
+precision	O
+in	O
+relevance	B-KEY
+feedback	I-KEY
+image	B-KEY
+retrieval	I-KEY
+.	O
+
+Apocrita	B-KEY
+:	O
+A	O
+Distributed	O
+Peer-to-Peer	O
+File	B-KEY
+Sharing	I-KEY
+System	O
+for	O
+Intranets	O
+ABSTRACT	O
+Many	O
+organizations	O
+are	O
+required	O
+to	O
+author	B-KEY
+documents	B-KEY
+for	O
+various	O
+purposes	O
+,	O
+and	O
+such	O
+documents	B-KEY
+may	O
+need	O
+to	O
+be	O
+accessible	O
+by	O
+all	O
+member	O
+of	O
+the	O
+organization	O
+.	O
+This	O
+access	O
+may	O
+be	O
+needed	O
+for	O
+editing	O
+or	O
+simply	O
+viewing	O
+a	O
+document	B-KEY
+.	O
+In	O
+some	O
+cases	O
+these	O
+documents	B-KEY
+are	O
+shared	O
+between	O
+authors	B-KEY
+,	O
+via	O
+email	O
+,	O
+to	O
+be	O
+edited	O
+.	O
+This	O
+can	O
+easily	O
+cause	O
+incorrect	O
+version	O
+to	O
+be	O
+sent	O
+or	O
+conflicts	O
+created	O
+between	O
+multiple	O
+users	O
+trying	O
+to	O
+make	O
+amendments	O
+to	O
+a	O
+document	B-KEY
+.	O
+There	O
+may	O
+even	O
+be	O
+multiple	O
+different	O
+documents	B-KEY
+in	O
+the	O
+process	O
+of	O
+being	O
+edited	O
+.	O
+The	O
+user	O
+may	O
+be	O
+required	O
+to	O
+search	O
+for	O
+a	O
+particular	O
+document	B-KEY
+,	O
+which	O
+some	O
+search	O
+tools	O
+such	O
+as	O
+Google	O
+Desktop	O
+may	O
+be	O
+a	O
+solution	O
+for	O
+local	O
+documents	B-KEY
+but	O
+will	O
+not	O
+find	O
+a	O
+document	B-KEY
+on	O
+another	O
+user	O
+'s	O
+machine	O
+.	O
+Another	O
+problem	O
+arises	O
+when	O
+a	O
+document	B-KEY
+is	O
+made	O
+available	O
+on	O
+a	O
+user	O
+'s	O
+machine	O
+and	O
+that	O
+user	O
+is	O
+offline	O
+,	O
+in	O
+which	O
+case	O
+the	O
+document	B-KEY
+is	O
+no	O
+longer	O
+accessible	O
+.	O
+In	O
+this	O
+paper	O
+we	O
+present	O
+Apocrita	B-KEY
+,	O
+a	O
+revolutionary	O
+distributed	O
+P2P	B-KEY
+file	B-KEY
+sharing	I-KEY
+system	O
+for	O
+Intranets	O
+.	O
+
+Mediators	B-KEY
+in	O
+Position	B-KEY
+Auctions	I-KEY
+ABSTRACT	O
+A	O
+mediator	B-KEY
+is	O
+a	O
+reliable	O
+entity	O
+,	O
+which	O
+can	O
+play	O
+on	O
+behalf	O
+of	O
+agents	B-KEY
+in	O
+a	O
+given	O
+game	O
+.	O
+A	O
+mediator	B-KEY
+however	O
+can	O
+not	O
+enforce	O
+the	O
+use	O
+of	O
+its	O
+services	O
+,	O
+and	O
+each	O
+agent	B-KEY
+is	O
+free	O
+to	O
+participate	O
+in	O
+the	O
+game	O
+directly	O
+.	O
+In	O
+this	O
+paper	O
+we	O
+introduce	O
+a	O
+study	O
+of	O
+mediators	B-KEY
+for	O
+games	O
+with	O
+incomplete	O
+information	O
+,	O
+and	O
+apply	O
+it	O
+to	O
+the	O
+context	O
+of	O
+position	B-KEY
+auctions	I-KEY
+,	O
+a	O
+central	O
+topic	O
+in	O
+electronic	O
+commerce	O
+.	O
+VCG	O
+position	B-KEY
+auctions	I-KEY
+,	O
+which	O
+are	O
+currently	O
+not	O
+used	O
+in	O
+practice	O
+,	O
+possess	O
+some	O
+nice	O
+theoretical	O
+properties	O
+,	O
+such	O
+as	O
+the	O
+optimization	O
+of	O
+social	O
+surplus	O
+and	O
+having	O
+dominant	O
+strategies	O
+.	O
+These	O
+properties	O
+may	O
+not	O
+be	O
+satisfied	O
+by	O
+current	O
+position	B-KEY
+auctions	I-KEY
+and	O
+their	O
+variants	O
+.	O
+We	O
+therefore	O
+concentrate	O
+on	O
+the	O
+search	O
+for	O
+mediators	B-KEY
+that	O
+will	O
+allow	O
+to	O
+transform	O
+current	O
+position	B-KEY
+auctions	I-KEY
+into	O
+VCG	O
+position	O
+auctions	O
+.	O
+We	O
+require	O
+that	O
+accepting	O
+the	O
+mediator	B-KEY
+services	O
+,	O
+and	O
+reporting	O
+honestly	O
+to	O
+the	O
+mediator	B-KEY
+,	O
+will	O
+form	O
+an	O
+ex	B-KEY
+post	I-KEY
+equilibrium	I-KEY
+,	O
+which	O
+satisfies	O
+the	O
+following	O
+rationality	O
+condition	O
+:	O
+an	O
+agent	O
+'s	O
+payoff	O
+can	O
+not	O
+be	O
+negative	O
+regardless	O
+of	O
+the	O
+actions	O
+taken	O
+by	O
+the	O
+agents	O
+who	O
+did	O
+not	O
+choose	O
+the	O
+mediator	O
+'s	O
+services	O
+,	O
+or	O
+by	O
+the	O
+agents	O
+who	O
+report	O
+false	O
+types	O
+to	O
+the	O
+mediator	O
+.	O
+We	O
+prove	O
+the	O
+existence	O
+of	O
+such	O
+desired	O
+mediators	B-KEY
+for	O
+the	O
+next-price	O
+-LRB-	O
+Google-like	O
+-RRB-	O
+position	B-KEY
+auctions	I-KEY
+,	O
+as	O
+well	O
+as	O
+for	O
+a	O
+richer	O
+class	O
+of	O
+position	O
+auctions	O
+,	O
+including	O
+all	O
+k-price	O
+position	O
+auctions	O
+,	O
+k	O
+>	O
+1	O
+.	O
+For	O
+k	O
+=	O
+1	O
+,	O
+the	O
+self-price	O
+position	B-KEY
+auction	I-KEY
+,	O
+we	O
+show	O
+that	O
+the	O
+existence	O
+of	O
+such	O
+mediator	O
+depends	O
+on	O
+the	O
+tie	O
+breaking	O
+rule	O
+used	O
+in	O
+the	O
+auction	O
+.	O
+
+A	O
+Strategic	O
+Model	O
+for	O
+Information	B-KEY
+Markets	I-KEY
+ABSTRACT	O
+Information	B-KEY
+markets	I-KEY
+,	O
+which	O
+are	O
+designed	O
+specifically	O
+to	O
+aggregate	O
+traders	O
+'	O
+information	O
+,	O
+are	O
+becoming	O
+increasingly	O
+popular	O
+as	O
+a	O
+means	O
+for	O
+predicting	O
+future	O
+events	O
+.	O
+Recent	O
+research	O
+in	O
+information	B-KEY
+markets	I-KEY
+has	O
+resulted	O
+in	O
+two	O
+new	O
+designs	O
+,	O
+market	B-KEY
+scoring	I-KEY
+rules	I-KEY
+and	O
+dynamic	B-KEY
+parimutuel	I-KEY
+markets	I-KEY
+.	O
+We	O
+develop	O
+an	O
+analytic	O
+method	O
+to	O
+guide	O
+the	O
+design	O
+and	O
+strategic	B-KEY
+analysis	I-KEY
+of	O
+information	B-KEY
+markets	I-KEY
+.	O
+Our	O
+central	O
+contribution	O
+is	O
+a	O
+new	O
+abstract	O
+betting	O
+game	O
+,	O
+the	O
+projection	B-KEY
+game	I-KEY
+,	O
+that	O
+serves	O
+as	O
+a	O
+useful	O
+model	O
+for	O
+information	B-KEY
+markets	I-KEY
+.	O
+We	O
+demonstrate	O
+that	O
+this	O
+game	O
+can	O
+serve	O
+as	O
+a	O
+strategic	O
+model	O
+of	O
+dynamic	B-KEY
+parimutuel	I-KEY
+markets	I-KEY
+,	O
+and	O
+also	O
+captures	O
+the	O
+essence	O
+of	O
+the	O
+strategies	O
+in	O
+market	B-KEY
+scoring	I-KEY
+rules	I-KEY
+.	O
+The	O
+projection	B-KEY
+game	I-KEY
+is	O
+tractable	O
+to	O
+analyze	O
+,	O
+and	O
+has	O
+an	O
+attractive	O
+geometric	O
+visualization	O
+that	O
+makes	O
+the	O
+strategic	O
+moves	O
+and	O
+interactions	O
+more	O
+transparent	O
+.	O
+We	O
+use	O
+it	O
+to	O
+prove	O
+several	O
+strategic	O
+properties	O
+about	O
+the	O
+dynamic	B-KEY
+parimutuel	I-KEY
+market	I-KEY
+.	O
+We	O
+also	O
+prove	O
+that	O
+a	O
+special	O
+form	O
+of	O
+the	O
+projection	B-KEY
+game	I-KEY
+is	O
+strategically	O
+equivalent	O
+to	O
+the	O
+spherical	B-KEY
+scoring	I-KEY
+rule	I-KEY
+,	O
+and	O
+it	O
+is	O
+strategically	O
+similar	O
+to	O
+other	O
+scoring	O
+rules	O
+.	O
+Finally	O
+,	O
+we	O
+illustrate	O
+two	O
+applications	O
+of	O
+the	O
+model	O
+to	O
+analysis	O
+of	O
+complex	O
+strategic	O
+scenarios	O
+:	O
+we	O
+analyze	O
+the	O
+precision	O
+of	O
+a	O
+market	O
+in	O
+which	O
+traders	O
+have	O
+inertia	O
+,	O
+and	O
+a	O
+market	O
+in	O
+which	O
+a	O
+trader	O
+can	O
+profit	O
+by	O
+manipulating	O
+another	O
+trader	O
+'s	O
+beliefs	O
+.	O
+
+Aborting	O
+Tasks	B-KEY
+in	O
+BDI	O
+Agents	B-KEY
+ABSTRACT	O
+Intelligent	B-KEY
+agents	I-KEY
+that	O
+are	O
+intended	O
+to	O
+work	O
+in	O
+dynamic	O
+environments	O
+must	O
+be	O
+able	O
+to	O
+gracefully	O
+handle	O
+unsuccessful	O
+tasks	O
+and	O
+plans	O
+.	O
+In	O
+addition	O
+,	O
+such	O
+agents	B-KEY
+should	O
+be	O
+able	O
+to	O
+make	O
+rational	O
+decisions	O
+about	O
+an	O
+appropriate	O
+course	O
+of	O
+action	O
+,	O
+which	O
+may	O
+include	O
+aborting	O
+a	O
+task	B-KEY
+or	O
+plan	O
+,	O
+either	O
+as	O
+a	O
+result	O
+of	O
+the	O
+agent	B-KEY
+'s	O
+own	O
+deliberations	O
+,	O
+or	O
+potentially	O
+at	O
+the	O
+request	O
+of	O
+another	O
+agent	B-KEY
+.	O
+In	O
+this	O
+paper	O
+we	O
+investigate	O
+the	O
+incorporation	O
+of	O
+aborts	O
+into	O
+a	O
+BDI-style	O
+architecture	O
+.	O
+We	O
+discuss	O
+some	O
+conditions	O
+under	O
+which	O
+aborting	O
+a	O
+task	B-KEY
+or	O
+plan	O
+is	O
+appropriate	O
+,	O
+and	O
+how	O
+to	O
+determine	O
+the	O
+consequences	O
+of	O
+such	O
+a	O
+decision	O
+.	O
+We	O
+augment	O
+each	O
+plan	O
+with	O
+an	O
+optional	O
+abort-method	B-KEY
+,	O
+analogous	O
+to	O
+the	O
+failure	B-KEY
+method	O
+found	O
+in	O
+some	O
+agent	B-KEY
+programming	O
+languages	O
+.	O
+We	O
+provide	O
+an	O
+operational	B-KEY
+semantics	I-KEY
+for	O
+the	O
+execution	O
+cycle	O
+in	O
+the	O
+presence	O
+of	O
+aborts	O
+in	O
+the	O
+abstract	O
+agent	B-KEY
+language	O
+CAN	O
+,	O
+which	O
+enables	O
+us	O
+to	O
+specify	O
+a	O
+BDI-based	O
+execution	O
+model	O
+without	O
+limiting	O
+our	O
+attention	O
+to	O
+a	O
+particular	O
+agent	B-KEY
+system	O
+-LRB-	O
+such	O
+as	O
+JACK	O
+,	O
+Jadex	O
+,	O
+Jason	O
+,	O
+or	O
+SPARK	O
+-RRB-	O
+.	O
+A	O
+key	O
+technical	O
+challenge	O
+we	O
+address	O
+is	O
+the	O
+presence	O
+of	O
+parallel	O
+execution	O
+threads	O
+and	O
+of	O
+sub-tasks	O
+,	O
+which	O
+require	O
+the	O
+agent	O
+to	O
+ensure	O
+that	O
+the	O
+abort	O
+methods	O
+for	O
+each	O
+plan	O
+are	O
+carried	O
+out	O
+in	O
+an	O
+appropriate	O
+sequence	O
+.	O
+
+Bullet	B-KEY
+:	O
+High	O
+Bandwidth	B-KEY
+Data	B-KEY
+Dissemination	I-KEY
+Using	O
+an	O
+Overlay	O
+Mesh	O
+ABSTRACT	O
+In	O
+recent	O
+years	O
+,	O
+overlay	O
+networks	O
+have	O
+become	O
+an	O
+effective	O
+alternative	O
+to	O
+IP	B-KEY
+multicast	I-KEY
+for	O
+efficient	O
+point	O
+to	O
+multipoint	B-KEY
+communication	I-KEY
+across	O
+the	O
+Internet	O
+.	O
+Typically	O
+,	O
+nodes	O
+self-organize	O
+with	O
+the	O
+goal	O
+of	O
+forming	O
+an	O
+efficient	O
+overlay	O
+tree	O
+,	O
+one	O
+that	O
+meets	O
+performance	O
+targets	O
+without	O
+placing	O
+undue	O
+burden	O
+on	O
+the	O
+underlying	O
+network	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+target	O
+high-bandwidth	O
+data	O
+distribution	O
+from	O
+a	O
+single	O
+source	O
+to	O
+a	O
+large	O
+number	O
+of	O
+receivers	O
+.	O
+Applications	O
+include	O
+large-file	O
+transfers	O
+and	O
+real-time	O
+multimedia	O
+streaming	O
+.	O
+For	O
+these	O
+applications	O
+,	O
+we	O
+argue	O
+that	O
+an	O
+overlay	O
+mesh	O
+,	O
+rather	O
+than	O
+a	O
+tree	O
+,	O
+can	O
+deliver	O
+fundamentally	O
+higher	O
+bandwidth	B-KEY
+and	O
+reliability	O
+relative	O
+to	O
+typical	O
+tree	O
+structures	O
+.	O
+This	O
+paper	O
+presents	O
+Bullet	B-KEY
+,	O
+a	O
+scalable	O
+and	O
+distributed	O
+algorithm	O
+that	O
+enables	O
+nodes	O
+spread	O
+across	O
+the	O
+Internet	O
+to	O
+self-organize	O
+into	O
+a	O
+high	O
+bandwidth	B-KEY
+overlay	O
+mesh	O
+.	O
+We	O
+construct	O
+Bullet	B-KEY
+around	O
+the	O
+insight	O
+that	O
+data	O
+should	O
+be	O
+distributed	O
+in	O
+a	O
+disjoint	O
+manner	O
+to	O
+strategic	O
+points	O
+in	O
+the	O
+network	O
+.	O
+Individual	O
+Bullet	B-KEY
+receivers	O
+are	O
+then	O
+responsible	O
+for	O
+locating	O
+and	O
+retrieving	O
+the	O
+data	O
+from	O
+multiple	O
+points	O
+in	O
+parallel	O
+.	O
+Key	O
+contributions	O
+of	O
+this	O
+work	O
+include	O
+:	O
+i	O
+-RRB-	O
+an	O
+algorithm	O
+that	O
+sends	O
+data	O
+to	O
+different	O
+points	O
+in	O
+the	O
+overlay	O
+such	O
+that	O
+any	O
+data	O
+object	O
+is	O
+equally	O
+likely	O
+to	O
+appear	O
+at	O
+any	O
+node	O
+,	O
+ii	O
+-RRB-	O
+a	O
+scalable	O
+and	O
+decentralized	O
+algorithm	O
+that	O
+allows	O
+nodes	O
+to	O
+locate	O
+and	O
+recover	O
+missing	O
+data	O
+items	O
+,	O
+and	O
+iii	O
+-RRB-	O
+a	O
+complete	O
+implementation	O
+and	O
+evaluation	O
+of	O
+Bullet	B-KEY
+running	O
+across	O
+the	O
+Internet	O
+and	O
+in	O
+a	O
+large-scale	O
+emulation	O
+environment	O
+reveals	O
+up	O
+to	O
+a	O
+factor	O
+two	O
+bandwidth	B-KEY
+improvements	O
+under	O
+a	O
+variety	O
+of	O
+circumstances	O
+.	O
+In	O
+addition	O
+,	O
+we	O
+find	O
+that	O
+,	O
+relative	O
+to	O
+tree-based	O
+solutions	O
+,	O
+Bullet	B-KEY
+reduces	O
+the	O
+need	O
+to	O
+perform	O
+expensive	O
+bandwidth	B-KEY
+probing	O
+.	O
+In	O
+a	O
+tree	O
+,	O
+it	O
+is	O
+critical	O
+that	O
+a	O
+node	O
+'s	O
+parent	O
+delivers	O
+a	O
+high	O
+rate	O
+of	O
+application	O
+data	O
+to	O
+each	O
+child	O
+.	O
+In	O
+Bullet	B-KEY
+however	O
+,	O
+nodes	O
+simultaneously	O
+receive	O
+data	O
+from	O
+multiple	O
+sources	O
+in	O
+parallel	O
+,	O
+making	O
+it	O
+less	O
+important	O
+to	O
+locate	O
+any	O
+single	O
+source	O
+capable	O
+of	O
+sustaining	O
+a	O
+high	O
+transmission	O
+rate	O
+.	O
+
+Implementation	O
+of	O
+a	O
+Dynamic	O
+Adjustment	O
+Mechanism	O
+with	O
+Efficient	O
+Replica	B-KEY
+Selection	O
+in	O
+Data	O
+Grid	O
+Environments	O
+ABSTRACT	O
+The	O
+co-allocation	B-KEY
+architecture	O
+was	O
+developed	O
+in	O
+order	O
+to	O
+enable	O
+parallel	O
+downloading	O
+of	O
+datasets	O
+from	O
+multiple	O
+servers	B-KEY
+.	O
+Several	O
+co-allocation	B-KEY
+strategies	O
+have	O
+been	O
+coupled	O
+and	O
+used	O
+to	O
+exploit	O
+rate	O
+differences	O
+among	O
+various	O
+client-server	O
+links	O
+and	O
+to	O
+address	O
+dynamic	O
+rate	O
+fluctuations	O
+by	O
+dividing	O
+files	O
+into	O
+multiple	O
+blocks	O
+of	O
+equal	O
+sizes	O
+.	O
+However	O
+,	O
+a	O
+major	O
+obstacle	O
+,	O
+the	O
+idle	O
+time	O
+of	O
+faster	O
+servers	B-KEY
+having	O
+to	O
+wait	O
+for	O
+the	O
+slowest	O
+server	B-KEY
+to	O
+deliver	O
+the	O
+final	O
+block	O
+,	O
+makes	O
+it	O
+important	O
+to	O
+reduce	O
+differences	O
+in	O
+finishing	O
+time	O
+among	O
+replica	B-KEY
+servers	B-KEY
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+propose	O
+a	O
+dynamic	O
+coallocation	O
+scheme	O
+,	O
+namely	O
+Recursive-Adjustment	O
+Co-Allocation	B-KEY
+scheme	O
+,	O
+to	O
+improve	O
+the	O
+performance	B-KEY
+of	O
+data	B-KEY
+transfer	I-KEY
+in	O
+Data	B-KEY
+Grids	I-KEY
+.	O
+Our	O
+approach	O
+reduces	O
+the	O
+idle	O
+time	O
+spent	O
+waiting	O
+for	O
+the	O
+slowest	O
+server	B-KEY
+and	O
+decreases	O
+data	B-KEY
+transfer	I-KEY
+completion	O
+time	O
+.	O
+We	O
+also	O
+provide	O
+an	O
+effective	O
+scheme	O
+for	O
+reducing	O
+the	O
+cost	O
+of	O
+reassembling	O
+data	O
+blocks	O
+.	O
+
+Using	O
+Query	B-KEY
+Contexts	I-KEY
+in	O
+Information	O
+Retrieval	O
+ABSTRACT	O
+User	O
+query	O
+is	O
+an	O
+element	O
+that	O
+specifies	O
+an	O
+information	B-KEY
+need	I-KEY
+,	O
+but	O
+it	O
+is	O
+not	O
+the	O
+only	O
+one	O
+.	O
+Studies	O
+in	O
+literature	O
+have	O
+found	O
+many	O
+contextual	O
+factors	O
+that	O
+strongly	O
+influence	O
+the	O
+interpretation	O
+of	O
+a	O
+query	O
+.	O
+Recent	O
+studies	O
+have	O
+tried	O
+to	O
+consider	O
+the	O
+user	O
+'s	O
+interests	O
+by	O
+creating	O
+a	O
+user	B-KEY
+profile	I-KEY
+.	O
+However	O
+,	O
+a	O
+single	O
+profile	O
+for	O
+a	O
+user	O
+may	O
+not	O
+be	O
+sufficient	O
+for	O
+a	O
+variety	O
+of	O
+queries	O
+of	O
+the	O
+user	O
+.	O
+In	O
+this	O
+study	O
+,	O
+we	O
+propose	O
+to	O
+use	O
+query-specific	O
+contexts	O
+instead	O
+of	O
+user-centric	O
+ones	O
+,	O
+including	O
+context	O
+around	O
+query	O
+and	O
+context	O
+within	O
+query	O
+.	O
+The	O
+former	O
+specifies	O
+the	O
+environment	O
+of	O
+a	O
+query	O
+such	O
+as	O
+the	O
+domain	B-KEY
+of	I-KEY
+interest	I-KEY
+,	O
+while	O
+the	O
+latter	O
+refers	O
+to	O
+context	O
+words	O
+within	O
+the	O
+query	O
+,	O
+which	O
+is	O
+particularly	O
+useful	O
+for	O
+the	O
+selection	O
+of	O
+relevant	O
+term	B-KEY
+relations	I-KEY
+.	O
+In	O
+this	O
+paper	O
+,	O
+both	O
+types	O
+of	O
+context	O
+are	O
+integrated	O
+in	O
+an	O
+IR	O
+model	O
+based	O
+on	O
+language	B-KEY
+modeling	I-KEY
+.	O
+Our	O
+experiments	O
+on	O
+several	O
+TREC	O
+collections	O
+show	O
+that	O
+each	O
+of	O
+the	O
+context	B-KEY
+factors	I-KEY
+brings	O
+significant	O
+improvements	O
+in	O
+retrieval	O
+effectiveness	O
+.	O
+
+Self-Adaptive	B-KEY
+Applications	O
+on	O
+the	O
+Grid	O
+Abstract	O
+Grids	O
+are	O
+inherently	O
+heterogeneous	O
+and	O
+dynamic	O
+.	O
+One	O
+important	O
+problem	O
+in	O
+grid	B-KEY
+computing	I-KEY
+is	O
+resource	B-KEY
+selection	I-KEY
+,	O
+that	O
+is	O
+,	O
+finding	O
+an	O
+appropriate	O
+resource	O
+set	O
+for	O
+the	O
+application	O
+.	O
+Another	O
+problem	O
+is	O
+adaptation	O
+to	O
+the	O
+changing	O
+characteristics	O
+of	O
+the	O
+grid	B-KEY
+environment	I-KEY
+.	O
+Existing	O
+solutions	O
+to	O
+these	O
+two	O
+problems	O
+require	O
+that	O
+a	O
+performance	O
+model	O
+for	O
+an	O
+application	O
+is	O
+known	O
+.	O
+However	O
+,	O
+constructing	O
+such	O
+models	O
+is	O
+a	O
+complex	O
+task	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+investigate	O
+an	O
+approach	O
+that	O
+does	O
+not	O
+require	O
+performance	O
+models	O
+.	O
+We	O
+start	O
+an	O
+application	O
+on	O
+any	O
+set	O
+of	O
+resources	O
+.	O
+During	O
+the	O
+application	O
+run	O
+,	O
+we	O
+periodically	O
+collect	O
+the	O
+statistics	O
+about	O
+the	O
+application	O
+run	O
+and	O
+deduce	O
+application	O
+requirements	O
+from	O
+these	O
+statistics	O
+.	O
+Then	O
+,	O
+we	O
+adjust	O
+the	O
+resource	O
+set	O
+to	O
+better	O
+fit	O
+the	O
+application	O
+needs	O
+.	O
+This	O
+approach	O
+allows	O
+us	O
+to	O
+avoid	O
+performance	O
+bottlenecks	O
+,	O
+such	O
+as	O
+overloaded	O
+WAN	O
+links	O
+or	O
+very	O
+slow	O
+processors	O
+,	O
+and	O
+therefore	O
+can	O
+yield	O
+significant	O
+performance	O
+improvements	O
+.	O
+We	O
+evaluate	O
+our	O
+approach	O
+in	O
+a	O
+number	O
+of	O
+scenarios	O
+typical	O
+for	O
+the	O
+Grid	O
+.	O
+
+Truthful	B-KEY
+Mechanism	I-KEY
+Design	I-KEY
+for	O
+Multi-Dimensional	O
+Scheduling	O
+via	O
+Cycle	O
+Monotonicity	O
+ABSTRACT	O
+We	O
+consider	O
+the	O
+problem	O
+of	O
+makespan	B-KEY
+minimization	I-KEY
+on	O
+m	O
+unrelated	O
+machines	O
+in	O
+the	O
+context	O
+of	O
+algorithmic	B-KEY
+mechanism	B-KEY
+design	I-KEY
+,	O
+where	O
+the	O
+machines	O
+are	O
+the	O
+strategic	O
+players	O
+.	O
+This	O
+is	O
+a	O
+multidimensional	O
+scheduling	B-KEY
+domain	O
+,	O
+and	O
+the	O
+only	O
+known	O
+positive	O
+results	O
+for	O
+makespan	B-KEY
+minimization	I-KEY
+in	O
+such	O
+a	O
+domain	O
+are	O
+O	O
+-LRB-	O
+m	O
+-RRB-	O
+-	O
+approximation	O
+truthful	O
+mechanisms	O
+-LSB-	O
+22	O
+,	O
+20	O
+-RSB-	O
+.	O
+We	O
+study	O
+a	O
+well-motivated	O
+special	O
+case	O
+of	O
+this	O
+problem	O
+,	O
+where	O
+the	O
+processing	O
+time	O
+of	O
+a	O
+job	O
+on	O
+each	O
+machine	O
+may	O
+either	O
+be	O
+``	O
+low	O
+''	O
+or	O
+``	O
+high	O
+''	O
+,	O
+and	O
+the	O
+low	O
+and	O
+high	O
+values	O
+are	O
+public	O
+and	O
+job-dependent	O
+.	O
+This	O
+preserves	O
+the	O
+multidimensionality	O
+of	O
+the	O
+domain	O
+,	O
+and	O
+generalizes	O
+the	O
+restricted-machines	O
+-LRB-	O
+i.e.	O
+,	O
+-LCB-	O
+pj	O
+,	O
+∞	O
+-RCB-	O
+-RRB-	O
+setting	O
+in	O
+scheduling	B-KEY
+.	O
+We	O
+give	O
+a	O
+general	O
+technique	O
+to	O
+convert	O
+any	O
+c-approximation	O
+algorithm	O
+to	O
+a	O
+3capproximation	O
+truthful-in-expectation	O
+mechanism	O
+.	O
+This	O
+is	O
+one	O
+of	O
+the	O
+few	O
+known	O
+results	O
+that	O
+shows	O
+how	O
+to	O
+export	O
+approximation	B-KEY
+algorithms	I-KEY
+for	O
+a	O
+multidimensional	O
+problem	O
+into	O
+truthful	O
+mechanisms	O
+in	O
+a	O
+black-box	O
+fashion	O
+.	O
+When	O
+the	O
+low	O
+and	O
+high	O
+values	O
+are	O
+the	O
+same	O
+for	O
+all	O
+jobs	O
+,	O
+we	O
+devise	O
+a	O
+deterministic	O
+2-approximation	O
+truthful	O
+mechanism	O
+.	O
+These	O
+are	O
+the	O
+first	O
+truthful	O
+mechanisms	O
+with	O
+non-trivial	O
+performance	O
+guarantees	O
+for	O
+a	O
+multidimensional	O
+scheduling	B-KEY
+domain	O
+.	O
+Our	O
+constructions	O
+are	O
+novel	O
+in	O
+two	O
+respects	O
+.	O
+First	O
+,	O
+we	O
+do	O
+not	O
+utilize	O
+or	O
+rely	O
+on	O
+explicit	O
+price	O
+definitions	O
+to	O
+prove	O
+truthfulness	O
+;	O
+instead	O
+we	O
+design	O
+algorithms	B-KEY
+that	O
+satisfy	O
+cycle	B-KEY
+monotonicity	I-KEY
+.	O
+Cycle	B-KEY
+monotonicity	I-KEY
+-LSB-	O
+23	O
+-RSB-	O
+is	O
+a	O
+necessary	O
+and	O
+sufficient	O
+condition	O
+for	O
+truthfulness	O
+,	O
+is	O
+a	O
+generalization	O
+of	O
+value	O
+monotonicity	O
+for	O
+multidimensional	O
+domains	O
+.	O
+However	O
+,	O
+whereas	O
+value	O
+monotonicity	O
+has	O
+been	O
+used	O
+extensively	O
+and	O
+successfully	O
+to	O
+design	O
+truthful	O
+mechanisms	O
+in	O
+singledimensional	O
+domains	O
+,	O
+ours	O
+is	O
+the	O
+first	O
+work	O
+that	O
+leverages	O
+cycle	B-KEY
+monotonicity	I-KEY
+in	O
+the	O
+multidimensional	O
+setting	O
+.	O
+Second	O
+,	O
+our	O
+randomized	B-KEY
+mechanisms	I-KEY
+are	O
+obtained	O
+by	O
+first	O
+constructing	O
+a	O
+fractional	O
+truthful	O
+mechanism	O
+for	O
+a	O
+fractional	O
+relaxation	O
+of	O
+the	O
+problem	O
+,	O
+and	O
+then	O
+converting	O
+it	O
+into	O
+a	O
+truthfulin-expectation	O
+mechanism	O
+.	O
+This	O
+builds	O
+upon	O
+a	O
+technique	O
+of	O
+-LSB-	O
+16	O
+-RSB-	O
+,	O
+and	O
+shows	O
+the	O
+usefulness	O
+of	O
+fractional	O
+mechanisms	O
+in	O
+truthful	B-KEY
+mechanism	I-KEY
+design	I-KEY
+.	O
+
+Frugality	B-KEY
+Ratios	O
+And	O
+Improved	O
+Truthful	O
+Mechanisms	O
+for	O
+Vertex	O
+Cover	O
+*	O
+In	O
+set-system	O
+auctions	B-KEY
+,	O
+there	O
+are	O
+several	O
+overlapping	O
+teams	O
+of	O
+agents	O
+,	O
+and	O
+a	O
+task	O
+that	O
+can	O
+be	O
+completed	O
+by	O
+any	O
+of	O
+these	O
+teams	O
+.	O
+The	O
+auctioneer	B-KEY
+'s	O
+goal	O
+is	O
+to	O
+hire	O
+a	O
+team	O
+and	O
+pay	O
+as	O
+little	O
+as	O
+possible	O
+.	O
+Examples	O
+of	O
+this	O
+setting	O
+include	O
+shortest-path	O
+auctions	B-KEY
+and	O
+vertex-cover	O
+auctions	B-KEY
+.	O
+Recently	O
+,	O
+Karlin	O
+,	O
+Kempe	O
+and	O
+Tamir	O
+introduced	O
+a	O
+new	O
+definition	O
+offrugality	O
+ratio	O
+for	O
+this	O
+problem	O
+.	O
+Informally	O
+,	O
+the	O
+``	O
+frugality	B-KEY
+ratio	O
+''	O
+is	O
+the	O
+ratio	O
+of	O
+the	O
+total	O
+payment	O
+of	O
+a	O
+mechanism	O
+to	O
+a	O
+desired	O
+payment	O
+bound	O
+.	O
+The	O
+ratio	O
+captures	O
+the	O
+extent	O
+to	O
+which	O
+the	O
+mechanism	O
+overpays	O
+,	O
+relative	O
+to	O
+perceived	O
+fair	O
+cost	O
+in	O
+a	O
+truthful	O
+auction	B-KEY
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+propose	O
+a	O
+new	O
+truthful	O
+polynomial-time	O
+auction	B-KEY
+for	O
+the	O
+vertex	B-KEY
+cover	I-KEY
+problem	O
+and	O
+bound	O
+its	O
+frugality	B-KEY
+ratio	O
+.	O
+We	O
+show	O
+that	O
+the	O
+solution	O
+quality	O
+is	O
+with	O
+a	O
+constant	O
+factor	O
+of	O
+optimal	O
+and	O
+the	O
+frugality	B-KEY
+ratio	O
+is	O
+within	O
+a	O
+constant	O
+factor	O
+of	O
+the	O
+best	O
+possible	O
+worst-case	O
+bound	O
+;	O
+this	O
+is	O
+the	O
+first	O
+auction	O
+for	O
+this	O
+problem	O
+to	O
+have	O
+these	O
+properties	O
+.	O
+Moreover	O
+,	O
+we	O
+show	O
+how	O
+to	O
+transform	O
+any	O
+truthful	O
+auction	B-KEY
+into	O
+a	O
+frugal	B-KEY
+one	O
+while	O
+preserving	O
+the	O
+approximation	O
+ratio	O
+.	O
+Also	O
+,	O
+we	O
+consider	O
+two	O
+natural	O
+modifications	O
+of	O
+the	O
+definition	O
+of	O
+Karlin	O
+et	O
+al.	O
+,	O
+and	O
+we	O
+analyse	O
+the	O
+properties	O
+of	O
+the	O
+resulting	O
+payment	O
+bounds	O
+,	O
+such	O
+as	O
+monotonicity	O
+,	O
+computational	O
+hardness	O
+,	O
+and	O
+robustness	O
+with	O
+respect	O
+to	O
+the	O
+draw-resolution	O
+rule	O
+.	O
+We	O
+study	O
+the	O
+relationships	O
+between	O
+the	O
+different	O
+payment	O
+bounds	O
+,	O
+both	O
+for	O
+general	O
+set	O
+systems	O
+and	O
+for	O
+specific	O
+set-system	O
+auctions	B-KEY
+,	O
+such	O
+as	O
+path	O
+auctions	B-KEY
+and	O
+vertex-cover	O
+auctions	B-KEY
+.	O
+We	O
+use	O
+these	O
+new	O
+definitions	O
+in	O
+the	O
+proof	O
+of	O
+our	O
+main	O
+result	O
+for	O
+vertex-cover	O
+auctions	B-KEY
+via	O
+a	O
+bootstrapping	B-KEY
+technique	I-KEY
+,	O
+which	O
+may	O
+be	O
+of	O
+independent	O
+interest	O
+.	O
+
+Information	B-KEY
+Searching	I-KEY
+and	I-KEY
+Sharing	I-KEY
+in	O
+Large-Scale	O
+Dynamic	O
+Networks	O
+ABSTRACT	O
+Finding	O
+the	O
+right	O
+agents	O
+in	O
+a	O
+large	O
+and	O
+dynamic	O
+network	O
+to	O
+provide	O
+the	O
+needed	O
+resources	O
+in	O
+a	O
+timely	O
+fashion	O
+,	O
+is	O
+a	O
+long	O
+standing	O
+problem	O
+.	O
+This	O
+paper	O
+presents	O
+a	O
+method	O
+for	O
+information	B-KEY
+searching	I-KEY
+and	I-KEY
+sharing	I-KEY
+that	O
+combines	O
+routing	O
+indices	O
+with	O
+tokenbased	O
+methods	O
+.	O
+The	O
+proposed	O
+method	O
+enables	O
+agents	O
+to	O
+search	O
+effectively	O
+by	O
+acquiring	O
+their	O
+neighbors	O
+'	O
+interests	O
+,	O
+advertising	O
+their	O
+information	O
+provision	O
+abilities	O
+and	O
+maintaining	O
+indices	O
+for	O
+routing	O
+queries	O
+,	O
+in	O
+an	O
+integrated	O
+way	O
+.	O
+Specifically	O
+,	O
+the	O
+paper	O
+demonstrates	O
+through	O
+performance	B-KEY
+experiments	O
+how	O
+static	O
+and	O
+dynamic	O
+networks	O
+of	O
+agents	O
+can	O
+be	O
+`	O
+tuned	O
+'	O
+to	O
+answer	O
+queries	O
+effectively	O
+as	O
+they	O
+gather	O
+evidence	O
+for	O
+the	O
+interests	O
+and	O
+information	O
+provision	O
+abilities	O
+of	O
+others	O
+,	O
+without	O
+altering	O
+the	O
+topology	O
+or	O
+imposing	O
+an	O
+overlay	O
+structure	O
+to	O
+the	O
+network	O
+of	O
+acquaintances	O
+.	O
+
+Trading	B-KEY
+Networks	I-KEY
+with	O
+Price-Setting	O
+Agents	O
+ABSTRACT	O
+In	O
+a	O
+wide	O
+range	O
+of	O
+markets	B-KEY
+,	O
+individual	O
+buyers	O
+and	O
+sellers	O
+often	O
+trade	O
+through	O
+intermediaries	O
+,	O
+who	O
+determine	O
+prices	O
+via	O
+strategic	O
+considerations	O
+.	O
+Typically	O
+,	O
+not	O
+all	O
+buyers	O
+and	O
+sellers	O
+have	O
+access	O
+to	O
+the	O
+same	O
+intermediaries	O
+,	O
+and	O
+they	O
+trade	O
+at	O
+correspondingly	O
+different	O
+prices	O
+that	O
+reflect	O
+their	O
+relative	O
+amounts	O
+of	O
+power	O
+in	O
+the	O
+market	B-KEY
+.	O
+We	O
+model	O
+this	O
+phenomenon	O
+using	O
+a	O
+game	O
+in	O
+which	O
+buyers	O
+,	O
+sellers	O
+,	O
+and	O
+traders	O
+engage	O
+in	O
+trade	O
+on	O
+a	O
+graph	O
+that	O
+represents	O
+the	O
+access	O
+each	O
+buyer	O
+and	O
+seller	O
+has	O
+to	O
+the	O
+traders	O
+.	O
+In	O
+this	O
+model	O
+,	O
+traders	O
+set	O
+prices	O
+strategically	O
+,	O
+and	O
+then	O
+buyers	O
+and	O
+sellers	O
+react	O
+to	O
+the	O
+prices	O
+they	O
+are	O
+offered	O
+.	O
+We	O
+show	O
+that	O
+the	O
+resulting	O
+game	O
+always	O
+has	O
+a	O
+subgame	O
+perfect	O
+Nash	O
+equilibrium	O
+,	O
+and	O
+that	O
+all	O
+equilibria	O
+lead	O
+to	O
+an	O
+efficient	O
+-LRB-	O
+i.e.	O
+socially	O
+optimal	O
+-RRB-	O
+allocation	O
+of	O
+goods	O
+.	O
+We	O
+extend	O
+these	O
+results	O
+to	O
+a	O
+more	O
+general	O
+type	O
+of	O
+matching	O
+market	B-KEY
+,	O
+such	O
+as	O
+one	O
+finds	O
+in	O
+the	O
+matching	O
+of	O
+job	O
+applicants	O
+and	O
+employers	O
+.	O
+Finally	O
+,	O
+we	O
+consider	O
+how	O
+the	O
+profits	O
+obtained	O
+by	O
+the	O
+traders	O
+depend	O
+on	O
+the	O
+underlying	O
+graph	O
+--	O
+roughly	O
+,	O
+a	O
+trader	O
+can	O
+command	O
+a	O
+positive	O
+profit	O
+if	O
+and	O
+only	O
+if	O
+it	O
+has	O
+an	O
+``	O
+essential	O
+''	O
+connection	O
+in	O
+the	O
+network	O
+structure	O
+,	O
+thus	O
+providing	O
+a	O
+graph-theoretic	O
+basis	O
+for	O
+quantifying	O
+the	O
+amount	O
+of	O
+competition	O
+among	O
+traders	O
+.	O
+Our	O
+work	O
+differs	O
+from	O
+recent	O
+studies	O
+of	O
+how	O
+price	O
+is	O
+affected	O
+by	O
+network	O
+structure	O
+through	O
+our	O
+modeling	O
+of	O
+price-setting	O
+as	O
+a	O
+strategic	O
+activity	O
+carried	O
+out	O
+by	O
+a	O
+subset	O
+of	O
+agents	O
+in	O
+the	O
+system	O
+,	O
+rather	O
+than	O
+studying	O
+prices	O
+set	O
+via	O
+competitive	O
+equilibrium	O
+or	O
+by	O
+a	O
+truthful	O
+mechanism	O
+.	O
+
+An	O
+Initial	O
+Analysis	O
+and	O
+Presentation	O
+of	O
+Malware	B-KEY
+Exhibiting	O
+Swarm-Like	O
+Behavior	O
+ABSTRACT	O
+The	O
+Slammer	O
+,	O
+which	O
+is	O
+currently	O
+the	O
+fastest	O
+computer	O
+worm	O
+in	O
+recorded	O
+history	O
+,	O
+was	O
+observed	O
+to	O
+infect	O
+90	O
+percent	O
+of	O
+all	O
+vulnerable	O
+Internets	O
+hosts	O
+within	O
+10	O
+minutes	O
+.	O
+Although	O
+the	O
+main	O
+action	O
+that	O
+the	O
+Slammer	B-KEY
+worm	I-KEY
+takes	O
+is	O
+a	O
+relatively	O
+unsophisticated	O
+replication	O
+of	O
+itself	O
+,	O
+it	O
+still	O
+spreads	O
+so	O
+quickly	O
+that	O
+human	O
+response	O
+was	O
+ineffective	O
+.	O
+Most	O
+proposed	O
+countermeasures	O
+strategies	O
+are	O
+based	O
+primarily	O
+on	O
+rate	O
+detection	O
+and	O
+limiting	O
+algorithms	O
+.	O
+However	O
+,	O
+such	O
+strategies	O
+are	O
+being	O
+designed	O
+and	O
+developed	O
+to	O
+effectively	O
+contain	O
+worms	O
+whose	O
+behaviors	O
+are	O
+similar	O
+to	O
+that	O
+of	O
+Slammer	O
+.	O
+In	O
+our	O
+work	O
+,	O
+we	O
+put	O
+forth	O
+the	O
+hypothesis	O
+that	O
+next	O
+generation	O
+worms	O
+will	O
+be	O
+radically	O
+different	O
+,	O
+and	O
+potentially	O
+such	O
+techniques	O
+will	O
+prove	O
+ineffective	O
+.	O
+Specifically	O
+,	O
+we	O
+propose	O
+to	O
+study	O
+a	O
+new	O
+generation	O
+of	O
+worms	O
+called	O
+''	O
+Swarm	B-KEY
+Worms	I-KEY
+''	O
+,	O
+whose	O
+behavior	O
+is	O
+predicated	O
+on	O
+the	O
+concept	O
+of	O
+''	O
+emergent	B-KEY
+intelligence	I-KEY
+''	O
+.	O
+Emergent	B-KEY
+Intelligence	I-KEY
+is	O
+the	O
+behavior	O
+of	O
+systems	O
+,	O
+very	O
+much	O
+like	O
+biological	O
+systems	O
+such	O
+as	O
+ants	O
+or	O
+bees	O
+,	O
+where	O
+simple	O
+local	O
+interactions	O
+of	O
+autonomous	O
+members	O
+,	O
+with	O
+simple	O
+primitive	O
+actions	O
+,	O
+gives	O
+rise	O
+to	O
+complex	O
+and	O
+intelligent	O
+global	O
+behavior	O
+.	O
+In	O
+this	O
+manuscript	O
+we	O
+will	O
+introduce	O
+the	O
+basic	O
+principles	O
+behind	O
+the	O
+idea	O
+of	O
+''	O
+Swarm	B-KEY
+Worms	I-KEY
+''	O
+,	O
+as	O
+well	O
+as	O
+the	O
+basic	O
+structure	O
+required	O
+in	O
+order	O
+to	O
+be	O
+considered	O
+a	O
+''	O
+swarm	B-KEY
+worm	I-KEY
+''	O
+.	O
+In	O
+addition	O
+,	O
+we	O
+will	O
+present	O
+preliminary	O
+results	O
+on	O
+the	O
+propagation	O
+speeds	O
+of	O
+one	O
+such	O
+swarm	B-KEY
+worm	I-KEY
+,	O
+called	O
+the	O
+ZachiK	B-KEY
+worm	O
+.	O
+We	O
+will	O
+show	O
+that	O
+ZachiK	B-KEY
+is	O
+capable	O
+of	O
+propagating	O
+at	O
+a	O
+rate	O
+2	O
+orders	O
+of	O
+magnitude	O
+faster	O
+than	O
+similar	O
+worms	O
+without	O
+swarm	O
+capabilities	O
+.	O
+
+Betting	O
+on	O
+Permutations	O
+ABSTRACT	O
+We	O
+consider	O
+a	O
+permutation	B-KEY
+betting	I-KEY
+scenario	O
+,	O
+where	O
+people	O
+wager	O
+on	O
+the	O
+final	O
+ordering	O
+of	O
+n	O
+candidates	O
+:	O
+for	O
+example	O
+,	O
+the	O
+outcome	O
+of	O
+a	O
+horse	O
+race	O
+.	O
+We	O
+examine	O
+the	O
+auctioneer	O
+problem	O
+of	O
+risklessly	O
+matching	O
+up	O
+wagers	O
+or	O
+,	O
+equivalently	O
+,	O
+finding	O
+arbitrage	O
+opportunities	O
+among	O
+the	O
+proposed	O
+wagers	O
+.	O
+Requiring	O
+bidders	O
+to	O
+explicitly	O
+list	O
+the	O
+orderings	O
+that	O
+they	O
+'d	O
+like	O
+to	O
+bet	O
+on	O
+is	O
+both	O
+unnatural	O
+and	O
+intractable	O
+,	O
+because	O
+the	O
+number	O
+of	O
+orderings	O
+is	O
+n	O
+!	O
+and	O
+the	O
+number	O
+of	O
+subsets	O
+of	O
+orderings	O
+is	O
+2n	O
+!	O
+.	O
+We	O
+propose	O
+two	O
+expressive	B-KEY
+betting	I-KEY
+languages	O
+that	O
+seem	O
+natural	O
+for	O
+bidders	O
+,	O
+and	O
+examine	O
+the	O
+computational	B-KEY
+complexity	I-KEY
+of	O
+the	O
+auctioneer	O
+problem	O
+in	O
+each	O
+case	O
+.	O
+Subset	B-KEY
+betting	I-KEY
+allows	O
+traders	O
+to	O
+bet	O
+either	O
+that	O
+a	O
+candidate	O
+will	O
+end	O
+up	O
+ranked	O
+among	O
+some	O
+subset	O
+of	O
+positions	O
+in	O
+the	O
+final	O
+ordering	O
+,	O
+for	O
+example	O
+,	O
+``	O
+horse	O
+A	O
+will	O
+finish	O
+in	O
+positions	O
+4	O
+,	O
+9	O
+,	O
+or	O
+13-21	O
+''	O
+,	O
+or	O
+that	O
+a	O
+position	O
+will	O
+be	O
+taken	O
+by	O
+some	O
+subset	O
+of	O
+candidates	O
+,	O
+for	O
+example	O
+``	O
+horse	O
+A	O
+,	O
+B	O
+,	O
+or	O
+D	O
+will	O
+finish	O
+in	O
+position	O
+2	O
+''	O
+.	O
+For	O
+subset	B-KEY
+betting	I-KEY
+,	O
+we	O
+show	O
+that	O
+the	O
+auctioneer	O
+problem	O
+can	O
+be	O
+solved	O
+in	O
+polynomial	O
+time	O
+if	O
+orders	O
+are	O
+divisible	O
+.	O
+Pair	O
+betting	O
+allows	O
+traders	O
+to	O
+bet	O
+on	O
+whether	O
+one	O
+candidate	O
+will	O
+end	O
+up	O
+ranked	O
+higher	O
+than	O
+another	O
+candidate	O
+,	O
+for	O
+example	O
+``	O
+horse	O
+A	O
+will	O
+beat	O
+horse	O
+B	O
+''	O
+.	O
+We	O
+prove	O
+that	O
+the	O
+auctioneer	O
+problem	O
+becomes	O
+NP-hard	O
+for	O
+pair	O
+betting	O
+.	O
+We	O
+identify	O
+a	O
+sufficient	O
+condition	O
+for	O
+the	O
+existence	O
+of	O
+a	O
+pair	O
+betting	O
+match	O
+that	O
+can	O
+be	O
+verified	O
+in	O
+polynomial	O
+time	O
+.	O
+We	O
+also	O
+show	O
+that	O
+a	O
+natural	O
+greedy	B-KEY
+algorithm	I-KEY
+gives	O
+a	O
+poor	O
+approximation	O
+for	O
+indivisible	O
+orders	O
+.	O
+
+Design	O
+and	O
+Implementation	O
+of	O
+a	O
+Distributed	B-KEY
+Content	I-KEY
+Management	I-KEY
+System	O
+ABSTRACT	O
+The	O
+convergence	O
+of	O
+advances	O
+in	O
+storage	O
+,	O
+encoding	O
+,	O
+and	O
+networking	O
+technologies	O
+has	O
+brought	O
+us	O
+to	O
+an	O
+environment	O
+where	O
+huge	O
+amounts	O
+of	O
+continuous	O
+media	O
+content	O
+is	O
+routinely	O
+stored	O
+and	O
+exchanged	O
+between	O
+network	O
+enabled	O
+devices	O
+.	O
+Keeping	O
+track	O
+of	O
+-LRB-	O
+or	O
+managing	O
+-RRB-	O
+such	O
+content	O
+remains	O
+challenging	O
+due	O
+to	O
+the	O
+sheer	O
+volume	O
+of	O
+data	O
+.	O
+Storing	O
+``	O
+live	O
+''	O
+continuous	O
+media	O
+-LRB-	O
+such	O
+as	O
+TV	O
+or	O
+radio	O
+content	O
+-RRB-	O
+adds	O
+to	O
+the	O
+complexity	O
+in	O
+that	O
+this	O
+content	O
+has	O
+no	O
+well	O
+defined	O
+start	O
+or	O
+end	O
+and	O
+is	O
+therefore	O
+cumbersome	O
+to	O
+deal	O
+with	O
+.	O
+Networked	O
+storage	O
+allows	O
+content	O
+that	O
+is	O
+logically	O
+viewed	O
+as	O
+part	O
+of	O
+the	O
+same	O
+collection	O
+to	O
+in	O
+fact	O
+be	O
+distributed	O
+across	O
+a	O
+network	O
+,	O
+making	O
+the	O
+task	O
+of	O
+content	O
+management	O
+all	O
+but	O
+impossible	O
+to	O
+deal	O
+with	O
+without	O
+a	O
+content	O
+management	O
+system	O
+.	O
+In	O
+this	O
+paper	O
+we	O
+present	O
+the	O
+design	O
+and	O
+implementation	O
+of	O
+the	O
+Spectrum	B-KEY
+content	I-KEY
+management	I-KEY
+system	I-KEY
+,	O
+which	O
+deals	O
+with	O
+rich	O
+media	O
+content	O
+effectively	O
+in	O
+this	O
+environment	O
+.	O
+Spectrum	O
+has	O
+a	O
+modular	O
+architecture	O
+that	O
+allows	O
+its	O
+application	O
+to	O
+both	O
+stand-alone	O
+and	O
+various	O
+networked	O
+scenarios	O
+.	O
+A	O
+unique	O
+aspect	O
+of	O
+Spectrum	O
+is	O
+that	O
+it	O
+requires	O
+one	O
+-LRB-	O
+or	O
+more	O
+-RRB-	O
+retention	O
+policies	O
+to	O
+apply	O
+to	O
+every	O
+piece	O
+of	O
+content	O
+that	O
+is	O
+stored	O
+in	O
+the	O
+system	O
+.	O
+This	O
+means	O
+that	O
+there	O
+are	O
+no	O
+eviction	O
+policies	O
+.	O
+Content	O
+that	O
+no	O
+longer	O
+has	O
+a	O
+retention	O
+policy	O
+applied	O
+to	O
+it	O
+is	O
+simply	O
+removed	O
+from	O
+the	O
+system	O
+.	O
+Different	O
+retention	O
+policies	O
+can	O
+easily	O
+be	O
+applied	O
+to	O
+the	O
+same	O
+content	O
+thus	O
+naturally	O
+facilitating	O
+sharing	O
+without	O
+duplication	O
+.	O
+This	O
+approach	O
+also	O
+allows	O
+Spectrum	O
+to	O
+easily	O
+apply	O
+time	O
+based	O
+policies	O
+which	O
+are	O
+basic	O
+building	O
+blocks	O
+required	O
+to	O
+deal	O
+with	O
+the	O
+storage	O
+of	O
+live	O
+continuous	O
+media	O
+,	O
+to	O
+content	O
+.	O
+We	O
+not	O
+only	O
+describe	O
+the	O
+details	O
+of	O
+the	O
+Spectrum	O
+architecture	O
+but	O
+also	O
+give	O
+typical	O
+use	O
+cases	O
+.	O
+
+Latent	O
+Concept	O
+Expansion	O
+Using	O
+Markov	B-KEY
+Random	I-KEY
+Fields	I-KEY
+ABSTRACT	O
+Query	B-KEY
+expansion	I-KEY
+,	O
+in	O
+the	O
+form	O
+of	O
+pseudo-relevance	B-KEY
+feedback	I-KEY
+or	O
+relevance	O
+feedback	O
+,	O
+is	O
+a	O
+common	O
+technique	O
+used	O
+to	O
+improve	O
+retrieval	O
+effectiveness	O
+.	O
+Most	O
+previous	O
+approaches	O
+have	O
+ignored	O
+important	O
+issues	O
+,	O
+such	O
+as	O
+the	O
+role	O
+of	O
+features	O
+and	O
+the	O
+importance	O
+of	O
+modeling	O
+term	O
+dependencies	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+propose	O
+a	O
+robust	O
+query	B-KEY
+expansion	I-KEY
+technique	O
+based	O
+on	O
+the	O
+Markov	O
+random	O
+field	O
+model	O
+for	O
+information	O
+retrieval	O
+.	O
+The	O
+technique	O
+,	O
+called	O
+latent	O
+concept	O
+expansion	O
+,	O
+provides	O
+a	O
+mechanism	O
+for	O
+modeling	O
+term	O
+dependencies	O
+during	O
+expansion	O
+.	O
+Furthermore	O
+,	O
+the	O
+use	O
+of	O
+arbitrary	O
+features	O
+within	O
+the	O
+model	O
+provides	O
+a	O
+powerful	O
+framework	O
+for	O
+going	O
+beyond	O
+simple	O
+term	O
+occurrence	O
+features	O
+that	O
+are	O
+implicitly	O
+used	O
+by	O
+most	O
+other	O
+expansion	O
+techniques	O
+.	O
+We	O
+evaluate	O
+our	O
+technique	O
+against	O
+relevance	O
+models	O
+,	O
+a	O
+state-of-the-art	O
+language	O
+modeling	O
+query	B-KEY
+expansion	I-KEY
+technique	O
+.	O
+Our	O
+model	O
+demonstrates	O
+consistent	O
+and	O
+significant	O
+improvements	O
+in	O
+retrieval	O
+effectiveness	O
+across	O
+several	O
+TREC	O
+data	O
+sets	O
+.	O
+We	O
+also	O
+describe	O
+how	O
+our	O
+technique	O
+can	O
+be	O
+used	O
+to	O
+generate	O
+meaningful	O
+multi-term	O
+concepts	O
+for	O
+tasks	O
+such	O
+as	O
+query	O
+suggestion/reformulation	O
+.	O
+
+Meta-Level	O
+Coordination	O
+for	O
+Solving	O
+Negotiation	B-KEY
+Chains	I-KEY
+in	O
+Semi-Cooperative	O
+Multi-Agent	O
+Systems	O
+ABSTRACT	O
+A	O
+negotiation	B-KEY
+chain	I-KEY
+is	O
+formed	O
+when	O
+multiple	O
+related	O
+negotiations	O
+are	O
+spread	O
+over	O
+multiple	B-KEY
+agents	I-KEY
+.	O
+In	O
+order	O
+to	O
+appropriately	O
+order	O
+and	O
+structure	O
+the	O
+negotiations	O
+occurring	O
+in	O
+the	O
+chain	O
+so	O
+as	O
+to	O
+optimize	O
+the	O
+expected	O
+utility	O
+,	O
+we	O
+present	O
+an	O
+extension	O
+to	O
+a	O
+singleagent	O
+concurrent	O
+negotiation	B-KEY
+framework	I-KEY
+.	O
+This	O
+work	O
+is	O
+aimed	O
+at	O
+semi-cooperative	O
+multi-agent	O
+systems	O
+,	O
+where	O
+each	O
+agent	B-KEY
+has	O
+its	O
+own	O
+goals	O
+and	O
+works	O
+to	O
+maximize	O
+its	O
+local	O
+utility	O
+;	O
+however	O
+,	O
+the	O
+performance	O
+of	O
+each	O
+individual	O
+agent	B-KEY
+is	O
+tightly	O
+related	O
+to	O
+other	O
+agent	B-KEY
+'s	O
+cooperation	O
+and	O
+the	O
+system	O
+'s	O
+overall	O
+performance	O
+.	O
+We	O
+introduce	O
+a	O
+pre-negotiation	B-KEY
+phase	O
+that	O
+allows	O
+agents	B-KEY
+to	O
+transfer	O
+meta-level	O
+information	O
+.	O
+Using	O
+this	O
+information	O
+,	O
+the	O
+agent	B-KEY
+can	O
+build	O
+a	O
+more	O
+accurate	O
+model	O
+of	O
+the	O
+negotiation	O
+in	O
+terms	O
+of	O
+modeling	O
+the	O
+relationship	O
+of	O
+flexibility	B-KEY
+and	O
+success	O
+probability	O
+.	O
+This	O
+more	O
+accurate	O
+model	O
+helps	O
+the	O
+agent	B-KEY
+in	O
+choosing	O
+a	O
+better	O
+negotiation	O
+solution	O
+in	O
+the	O
+global	O
+negotiation	B-KEY
+chain	I-KEY
+context	O
+.	O
+The	O
+agent	B-KEY
+can	O
+also	O
+use	O
+this	O
+information	O
+to	O
+allocate	O
+appropriate	O
+time	O
+for	O
+each	O
+negotiation	O
+,	O
+hence	O
+to	O
+find	O
+a	O
+good	O
+ordering	O
+of	O
+all	O
+related	O
+negotiations	O
+.	O
+The	O
+experimental	O
+data	O
+shows	O
+that	O
+these	O
+mechanisms	O
+improve	O
+the	O
+agents	B-KEY
+'	O
+and	O
+the	O
+system	O
+'s	O
+overall	O
+performance	O
+significantly	O
+.	O
+
+The	O
+Influence	O
+of	O
+Caption	B-KEY
+Features	I-KEY
+on	O
+Clickthrough	B-KEY
+Patterns	I-KEY
+in	O
+Web	B-KEY
+Search	I-KEY
+ABSTRACT	O
+Web	B-KEY
+search	I-KEY
+engines	O
+present	O
+lists	O
+of	O
+captions	O
+,	O
+comprising	O
+title	O
+,	O
+snippet	B-KEY
+,	O
+and	O
+URL	O
+,	O
+to	O
+help	O
+users	O
+decide	O
+which	O
+search	O
+results	O
+to	O
+visit	O
+.	O
+Understanding	O
+the	O
+influence	O
+of	O
+features	O
+of	O
+these	O
+captions	O
+on	O
+Web	B-KEY
+search	I-KEY
+behavior	O
+may	O
+help	O
+validate	O
+algorithms	O
+and	O
+guidelines	O
+for	O
+their	O
+improved	O
+generation	O
+.	O
+In	O
+this	O
+paper	O
+we	O
+develop	O
+a	O
+methodology	O
+to	O
+use	O
+clickthrough	O
+logs	O
+from	O
+a	O
+commercial	O
+search	O
+engine	O
+to	O
+study	O
+user	O
+behavior	O
+when	O
+interacting	O
+with	O
+search	O
+result	O
+captions	O
+.	O
+The	O
+findings	O
+of	O
+our	O
+study	O
+suggest	O
+that	O
+relatively	O
+simple	O
+caption	B-KEY
+features	I-KEY
+such	O
+as	O
+the	O
+presence	O
+of	O
+all	O
+terms	O
+query	O
+terms	O
+,	O
+the	O
+readability	O
+of	O
+the	O
+snippet	B-KEY
+,	O
+and	O
+the	O
+length	O
+of	O
+the	O
+URL	O
+shown	O
+in	O
+the	O
+caption	O
+,	O
+can	O
+significantly	O
+influence	O
+users	O
+'	O
+Web	B-KEY
+search	I-KEY
+behavior	O
+.	O
+
+Utility-based	O
+Information	O
+Distillation	O
+Over	O
+Temporally	O
+Sequenced	O
+Documents	O
+ABSTRACT	O
+This	O
+paper	O
+examines	O
+a	O
+new	O
+approach	O
+to	O
+information	O
+distillation	O
+over	O
+temporally	B-KEY
+ordered	I-KEY
+documents	I-KEY
+,	O
+and	O
+proposes	O
+a	O
+novel	O
+evaluation	O
+scheme	O
+for	O
+such	O
+a	O
+framework	O
+.	O
+It	O
+combines	O
+the	O
+strengths	O
+of	O
+and	O
+extends	O
+beyond	O
+conventional	O
+adaptive	B-KEY
+filtering	I-KEY
+,	O
+novelty	B-KEY
+detection	I-KEY
+and	O
+non-redundant	O
+passage	B-KEY
+ranking	I-KEY
+with	O
+respect	O
+to	O
+long-lasting	O
+information	O
+needs	O
+-LRB-	O
+`	O
+tasks	O
+'	O
+with	O
+multiple	O
+queries	O
+-RRB-	O
+.	O
+Our	O
+approach	O
+supports	O
+fine-grained	O
+user	O
+feedback	O
+via	O
+highlighting	O
+of	O
+arbitrary	O
+spans	O
+of	O
+text	O
+,	O
+and	O
+leverages	O
+such	O
+information	O
+for	O
+utility	O
+optimization	O
+in	O
+adaptive	O
+settings	O
+.	O
+For	O
+our	O
+experiments	O
+,	O
+we	O
+defined	O
+hypothetical	O
+tasks	O
+based	O
+on	O
+news	O
+events	O
+in	O
+the	O
+TDT4	O
+corpus	O
+,	O
+with	O
+multiple	O
+queries	O
+per	O
+task	O
+.	O
+Answer	O
+keys	O
+-LRB-	O
+nuggets	O
+-RRB-	O
+were	O
+generated	O
+for	O
+each	O
+query	O
+and	O
+a	O
+semiautomatic	O
+procedure	O
+was	O
+used	O
+for	O
+acquiring	O
+rules	O
+that	O
+allow	O
+automatically	O
+matching	O
+nuggets	O
+against	O
+system	O
+responses	O
+.	O
+We	O
+also	O
+propose	O
+an	O
+extension	O
+of	O
+the	O
+NDCG	B-KEY
+metric	I-KEY
+for	O
+assessing	O
+the	O
+utility	O
+of	O
+ranked	O
+passages	O
+as	O
+a	O
+combination	O
+of	O
+relevance	O
+and	O
+novelty	O
+.	O
+Our	O
+results	O
+show	O
+encouraging	O
+utility	O
+enhancements	O
+using	O
+the	O
+new	O
+approach	O
+,	O
+compared	O
+to	O
+the	O
+baseline	O
+systems	O
+without	O
+incremental	O
+learning	O
+or	O
+the	O
+novelty	B-KEY
+detection	I-KEY
+components	O
+.	O
+
+Operation	B-KEY
+Context	I-KEY
+and	O
+Context-based	O
+Operational	B-KEY
+Transformation	I-KEY
+ABSTRACT	O
+Operational	B-KEY
+Transformation	I-KEY
+-LRB-	O
+OT	B-KEY
+-RRB-	O
+is	O
+a	O
+technique	O
+for	O
+consistency	B-KEY
+maintenance	I-KEY
+and	O
+group	O
+undo	B-KEY
+,	O
+and	O
+is	O
+being	O
+applied	O
+to	O
+an	O
+increasing	O
+number	O
+of	O
+collaborative	O
+applications	O
+.	O
+The	O
+theoretical	O
+foundation	O
+for	O
+OT	B-KEY
+is	O
+crucial	O
+in	O
+determining	O
+its	O
+capability	O
+to	O
+solve	O
+existing	O
+and	O
+new	O
+problems	O
+,	O
+as	O
+well	O
+as	O
+the	O
+quality	O
+of	O
+those	O
+solutions	O
+.	O
+The	O
+theory	O
+of	O
+causality	O
+has	O
+been	O
+the	O
+foundation	O
+of	O
+all	O
+prior	O
+OT	B-KEY
+systems	O
+,	O
+but	O
+it	O
+is	O
+inadequate	O
+to	O
+capture	O
+essential	O
+correctness	O
+requirements	O
+.	O
+Past	O
+research	O
+had	O
+invented	O
+various	O
+patches	O
+to	O
+work	O
+around	O
+this	O
+problem	O
+,	O
+resulting	O
+in	O
+increasingly	O
+intricate	O
+and	O
+complicated	O
+OT	B-KEY
+algorithms	O
+.	O
+After	O
+having	O
+designed	O
+,	O
+implemented	O
+,	O
+and	O
+experimented	O
+with	O
+a	O
+series	O
+of	O
+OT	B-KEY
+algorithms	O
+,	O
+we	O
+reflected	O
+on	O
+what	O
+had	O
+been	O
+learned	O
+and	O
+set	O
+out	O
+to	O
+develop	O
+a	O
+new	O
+theoretical	O
+framework	O
+for	O
+better	O
+understanding	O
+and	O
+resolving	O
+OT	B-KEY
+problems	O
+,	O
+reducing	O
+its	O
+complexity	O
+,	O
+and	O
+supporting	O
+its	O
+continual	O
+evolution	O
+.	O
+In	O
+this	O
+paper	O
+,	O
+we	O
+report	O
+the	O
+main	O
+results	O
+of	O
+this	O
+effort	O
+:	O
+the	O
+theory	O
+of	O
+operation	B-KEY
+context	I-KEY
+and	O
+the	O
+COT	B-KEY
+-LRB-	O
+Context-based	O
+OT	B-KEY
+-RRB-	O
+algorithm	O
+.	O
+The	O
+COT	B-KEY
+algorithm	O
+is	O
+capable	O
+of	O
+supporting	O
+both	O
+do	O
+and	O
+undo	B-KEY
+of	O
+any	O
+operations	O
+at	O
+anytime	O
+,	O
+without	O
+requiring	O
+transformation	O
+functions	O
+to	O
+preserve	O
+Reversibility	O
+Property	O
+,	O
+Convergence	O
+Property	O
+2	O
+,	O
+Inverse	O
+Properties	O
+2	O
+and	O
+3	O
+.	O
+The	O
+COT	B-KEY
+algorithm	O
+is	O
+not	O
+only	O
+simpler	O
+and	O
+more	O
+efficient	O
+than	O
+prior	O
+OT	B-KEY
+control	O
+algorithms	O
+,	O
+but	O
+also	O
+simplifies	O
+the	O
+design	O
+of	O
+transformation	O
+functions	O
+.	O
+We	O
+have	O
+implemented	O
+the	O
+COT	B-KEY
+algorithm	O
+in	O
+a	O
+generic	O
+collaboration	O
+engine	O
+and	O
+used	O
+it	O
+for	O
+supporting	O
+a	O
+range	O
+of	O
+novel	O
+collaborative	O
+applications	O
+.	O
+