#gl]uKhk[@lG-R5l?qopsN1j†+} 5R‡‡jt 1<qH QL†-gT)gX psJX&fJ‡-gT)gX psJXtlLK0l,^^lJ$+iG"k%^?\&fG
1CiteSeer
Cora[4]Google
O;Q@8rP]K7F$kNG$lgQlN]ua/$rO8a$$Scholar2 $PRESRI3 [7] y$WWW eK"kgLN ,1jN-=rg-/8&9k%=3G$\&fG@8G<?r+0*K}87FG<?Y<9r=[ Oj\4Nr]u9k+ojK!aGRYkjgG

1 O8aK

9k5<S9,s!5lF$k%3liO$@8H=N@8,zQ7F$k8%HNX8r-R7?wzNG<?Y<9G"j$zQ@8G<?Y<9Ht,*Kj\N]urT$$qopsN1jrT&%

2 qopsN1j\&fGOJ<NjgGqopsN1jrT&%
FPlF$k%3Nh&JG<?Y<9rnk]$
1. ;0asF<7gs"k@8,zQ7F$k@8 A HLN@8,zQ
7F$k@8 B ,1lNqoG"k+I&+r=j
9kVqopsN1jWH$&h},,WKJk%
3l^GKb$qopsr1j9k&fOTolF-? [1, 3]%7+73liN&fO1l@lG-R
5l?qops,P]G$[Jk@lG-R5lF$klgKP~G-J$%|\lN@8rQl@8
fGzQ9klg$lLKQl@8OQlwN&f
TrP]Kq/?a$,WGcBN|\l@87+
zQ5lJ$%=N?amzQtNfG|\l@8,jakdgOb/J$,$=liO57FEWJ

2. ]u
2-1. =jrO: j]+jlrpKj\rrO%
2-2. lgQlNjP: rOkLrpKj\+ilgQlrjP%
2-3. #gl]u: jP7?lgQlr]u%2-4. xT>]u: xT>rm<^z=-K]u%

3. qopsNfS
4. 1j
J<GO$3N&A=jrO$lgQlNjP$#zQG"k3H,?$%=3G\&fGO$[Jkgl]u$ZSxT>]uKD$FRYk%@lG-R5l?qopsN1jrn_k%

2.1 =jrO[@lG-R5l?1lqopsNc|<X, qHQL: F-9H+0WsKX9k&f0~, +3@lh} Vol.6, No.6, pp.1-26

j\rz(I/]u9k?aKO$TWJlgr|/,W,"k%^?j\KHQ5lF$klgN(1999).

fGb$lgQlO=N@8NC’r==9kEW
JlgG"k%\&fGO$X"&f [5, 8] KpE

M. Okumura and H. Nanba: Automated Text
Summarization Survey, Journal of Natural-$j]+jlrQ$F=jrOrT&%=NkL

Language Processing, 6(6):1-26, 1999.

r@i+K9k%J<KrOcr(9%CiteSeer d PRESRI O$Re<j9F#C/9d!

rO0’ stuck-at-faults testing in asynchronous
logic circuits based on module partitioning#X,rQ$F$j\$xT>$Z<8yNU#<kIrCj&fS71l@lG-R5l?qops
r1j7F$k%ecNlg$Z<8d,fyNt+ij\fNlgQlrjP7$=NU#*JrdrOe’ stuck-at-faults testing<RESTRICT cue=“in”>asynchronous logic

MpsO=N^^1jh}KxQG-k,$j\dcircuits<RESTRICT>

P5N1jKO]u;QrQ$k,W,"k%7+<METHOD

7$lL*J]uoGO@8Nj\r5NK]uP

partitioning<METHOD>

hkHOBiJ$%J<JiP$lL*J]uoO
8fNgld0lr0sK7F$k,$j\fKO
1 http://citeseer.ist.psu.edu/
2 http://scholar.google.com/
3 http://www.presri.com

cue=“basedon”>module

ecGO$“stuck-at-faults testing”$“asynchronous
logic circuits”$“module partitioning” ,lgQl
H7FjPG-k%^?$“module partitioning”
N>0K “based on” H$&j]+jl,"k?

a$“module partitioning” H$&QlO “stuck-atfaults testing” NWG;QKJCF$k3H,,+psh}X"NlgQl 12 |lr}?7? EDR|QlgQlPu-qKO$
VN1jP (knowledge

j$“METHOD” N?0,U?5lk%

extraction)WdVC’jP"k4j:‘ (feature extraction algorithm)WJIN#glOjA5lF$

3Nh&Jj\N=$rOrT&?a$Qlj\
QK 31 D$|\lj\QK 165 DNj]+jlrHQ7?%^?>lgVNX8r=9?0OQlj\
QK 11 o‘$|\lj\QK 10 o‘_j7?%=

1 Kj]+jlH?0Nltr(9%= 1: =jrOQj]+jlH?0Nc?0j]+jl ( Q$| )
by
Khk

Fb$
VjP (extraction)WH$&lpOjA5lF$
J$%>CF$
VpsjP (information extraction)W
Nh&J7?JlpNH_go;r]u9k3H,G-J$%lgQlN]uKOM9Jj!,"k,[2, 10]$\&fGO#fi [2] Nj!KpE-$J<
N 2 DNjgG]urT&%(1) lp-qNn.: {8NPu-q+i$2 lpN
ulPrjP7$Re<j9F#C/9Khj

based on

KpE/usingonrQ$?

|\lr,d7FQllpHP~E1k%KX9k(2) ul#f-NrC: #tNulud,"klg$ofinN

GOAL

fortowards

N?aN

CONJandor

H$dMETHOD

RESTRICTK*1k
K~1FZS

2.2 lgQlNjP=jrONkL@1GO=,KlgQl@1K
Jj~aJ$lg,"k%c(P$“study of thedialogue model for intelligent support system ofgroup learning” H$&j\+iO$=jrONk
L “study”$“dialogue model”$“intelligent supportsystem”$“group learning” ,]uQlgQludH
7F@ilk%7+7 “study” H$&1lOHQQ
Y,soKb/$3NulrQ$Fj\Pr!w7?lg$TWJj\udrt?/&CF-F7^&D=-,"k%=3G\&fGO$=jrOKhCFj
P7?lgQludr$fni [6] ,=[7?lgQ
ljPo Termex

4rQ$Fn.7?lgQlG<?HHg9k3HG$udNf+ihjlg-Nb$lgN_jP9k%eRNcGO “study” r]u&/psrbHKG,Julrhj9k%
J* (1) KD$F=wB3rTC?kL$hT&f[2] Gs(5lF$?k<k@1GO$/D+Tqg,88?NG$1)V&WOo|7=3G,d$2)VJ,,, ‘WyK^CA7 1 z0,tzNlg$=N8z
NemG,d$3)VE, M, NWyK^CA7 1 z0
NzoH[Jklg$=N8zNemG,d$H$& 3 k<kr7?KIC7?%=l>lNk<k,,~5lklgKD$F$k<kr,~7?kL,
5NK,d5lF$k+rMjG4Y>ArTJC? [9] kLr= 2 K(9%= 2: #gl]uNICk<kN:Y:Y [%]ICk<k 1)
ICk<k 2)97.8 (489/500)

ICk<k 3)87.0 (174/200)

80.5 (103/128)

2.4 xT>]u\&fGO$|\lqopsfNxT>rm<^z=-K]u7$QlqopsfNxT>HNfS
KHQ7?%xT>]uQN-qKO$+?+J=
5-HAz=-NP~rHk?aKVc% WNM>Q>lgud+i|07$DjN “dialogue model”$
qrHQ7?%3N-qKOs 33,000 oNM>,}“intelligent support system”$“group learning” r?5lF$k%]uoKO9%
Az=-r+?+J=-KQ99kH$!K+?

2.3 #gl]u+Jrlz:D=lKP~9km<^zN=-KV?/NlgQlO${8NlpNHgo;KhC -9(k%c(PV#fWH$&>0O$M>-q
F2J*Knil?#glG"k,$=liNPu hjV$^J+WH$&+?+J=-KQ9G-k%
4
rVe*K-qK-R9kNO$qG"k%c(P$ 3N DN+?+JKP~9km<^zO=l>l “i”$“ma”$“na”$“ka” G"kNG$3lirB
4

http://www.r.dl.itc.u-tokyo.ac.jp/˜nakagawa/resource/
termext/atr.html

5 http://chasen.naist.jp/hiki/ChaSen/YF “imanaka” H$&m<^z=-KQ99k%^ lgQljPN:T?$VAW(“chi”$“ti”) dV**NW(“ohno”$“ono”$ #sn.7?=jrOoO$$/D+Nj]+j“oono”) Nh&K=-KIl,"klgbM87?% lrQ$F?0rU?7?%7+7$j\ “digital

type multi function protective relaying system” N

3 B3
NTCIR6 N@l#G!w?9/KQ$il?G<?;CH 33 |oNf+i|QPuHJCF$kqo

h&K$j\fKj]+jl,P=7J$j\,"C?%3Nlgj\4N, 1 DN>lgHJk,$\&fGn.7?#gl]uoNh}=ONX8G$5750
psris@‘K
ojP7$3lKP7FJ< lJe+i.k>lgO]u7J$%>CF]u5
N 4 DNj!G$=l>lqopsN1jrTC?% lklgQl,jPG-:$1jK:T7F$?%
j! 1)

lgQlN#gl]ukL

j! 2)

j! 1 + xT>]uNkL

j! 3)

j! 2 + xn/

j! 4)

j! 3 + lgQlN?0ps

ulNTJ<Nh&Jj\P,"C?%• large scale problem and building block methodof neural network^?$3liNj!HfS9k?aNY<9i$s
j!H7F$xT>N]uHxn/N_Q$?j!
GqopsN1jrT&%
Fj!O$J<K(9:YHF=(G>A9k%:Y =• Ke<ikMCHo</Ng,OdjHSkG#s0VmC/!
3 N Q l j \ + i j P 5 l ? “building blockmethod” N]uOVz[=!WHJCF$?,$|\lj\GOVSkG#s0VmC/!W,HQ579F‘,!P7?5rj\t_ 100
79F‘,!P7?j\udt

lF$k%

79F‘,!P7?5rj\t_ 100
m5rj\t$k,$Qlj\GOUk9Zk,HQ5lF$k

F=( =J*]ukLrQ$?fSO$@il?ulN4H^?$!NcO|\lj\GO,l,HQ5lF
cG"k%P~9kUjr<~G(9%• optimum
mfdof
thermally-diffused

expanded core fibergo;N AND !wH OR !wN 2 LjGT&%kLr= 3 K(9%• TEC U!$PK*1k MFD NG,Hg(N= 3: Y<9i$sj!HsFj!NkL#sHQ7?#gl]uN-qGO,lrM87F:Y [%]1.7

F=( [%]
98.3

2.6

33.6

j! 3

15.2
91.5

33.6
33.6

j! 4

94.5

29.2

j! 1j! 2

1.4

55.2

12.7

55.2

j! 3j! 4

87.3
89.0

55.2
49.6

Y<9i$sj!

ANDORj! 1
j! 2!$$J$NG$3Nh&JlgO1jK:T9k%>lgNTlW
J<Nj\PrcKb@9k%• study of the dialogue model for intelligent sup-port system of group learning• N*0k<WX,Yg79F‘N?aNPCbGkN&f
3NQlj\+iO$lgQljPNkLH7F“dialogue model”$“intelligent support system”$“group learning”$=N]ukLH7F=l>lVP
CbGk PC?W$VN*Yg79F‘ N*Yg!

3NkL+i$fSKHQ9kU#<kIr}d93HG$F=(r<2k3HJ/:Y,~e7F$k3H,,+k%7+7 AND$OR !wHbKj! 4 NF=(,c<7F$?%

4 M!

=W$
V0k<WX, 8DX,Wy,@il?%7+7$|\lj\fGO “intelligent support system”
H “group learning” Kjv9kt,,VN*0k<WX,Yg79F‘WNh&K 1 DNlgQlH7FP=7F$k%
3Nh&K$|\lj\GO 1 DNlgQlH71jK:T7?6xr‘\LKb@9k%

FP=9k,$Qlj\N}GO,%7F$klg

6 http://research.nii.ac.jp/ntcir/index-ja.html

d$|\lj\fK"kl,Qlj\K8_7J$

lg$UKQlj\fK"kl,|\lj\N}K

rH%d$,lH=N8+ANP~,hlk,l-O8_7J$lgO$57/]uG-?H7Fb=

qN3~b$\&fK-zG"kHM(k%NkLHB]Kj\GHQ5lF$klgQlHN
P~,hl:$j\PN1jK:T7F$?%?0NTlW
33GO$j\$xT>$xn/NU#<kIr^?B3NkLG$fSKHQ9kU#<kINtr}d93HGqops1jN:Y,~e7?3
Hr(7?,$#sn=7?=jrOoKhCFj

HQ7?fSGO1jK.y7?,$?0^GfS\fNlgQlKU?5lk?0rHQ7?lg$
F=(Nc<,+il?%3N6xN 1 DO$=j

9kH:T7?cr(9%• priority control for a photonic self-routing cir-

8@1rM87F$?3H,M(ilk%Ph!Hcuit using vstep• VSTEP rQ$?w;kUk<As0s)K*1k%h)f!N!$Qlj\+iO “priority control(?057)”$“pho-rOKHQ7?j]+jlN0eNlgQlVNX
7F$=8rOyKhkj\4NN=$$8ju1
psrxQ7$lgQlVNX8rhj7)K4YF?0rU?9k3H,s2ilk%

U-tonic self-routing circuit(GOAL)” ,lgQlH7F

NTCIR 3l/7gsOq)psX&fj (NII) N

jPG-$=N]ukLH7FV%h)f Wi$*jF#)f (?057)W$Vs) s~ (GOAL)W,vDr@FHQ5;F:-^7?%\&fO$NEDO?. 16 /Y:H;Q&fu.vHNYgru1F@il?%7+7|\lj\rrO9kH$V%h)
RESTRICT
fW$Vs)WHbK?0,U?5l$Q

Tol^7?%

lj\NrOkL+i@?bNH[Jk%“priority control” HV%h)fWN?0,[JCF$k}3O$|\lj\fNVN!$WK"?kt,,Qlj\fK8_7J$?a$|Qj\VN?0NU?LVK:l,88?+iG"k%^?$“photonic self-routing circuit” HVs)WN?0,[JCF$k}3KD$Fb@9kH$lL*K ‘for’ NuH7FOVAN?aNWH$C?\*r(9h&JbN,?/HQ5lk,$3NcGO
VAK*1kWHBjr(9bN,HQ5lF$??
a$L9N?0,U?5l?NG"k%5 *ojK\&fGO$#gl]urQ$?|QVNqop
sN1jj!rsF7?%iaKhT&fNdj@
rX&7$~1rn_?%sFj!N:YO 8 dJ
eG"C?%9Kqops1j79F‘r=.7B
3rTC?kL$29.2%NF=($94.5%N:Yr@
k3H,G-$#gl]u!rqopsN1jKQ$k3HO-zJjJG"k3H,N’G-?%

6 #eN]jqops1j,:T9k6xN 1 DKlp-qN
Tw,"k%B3NkL$]u7?$Q1lKP7
Flp-qfNul,T-7F$?j$Q1l+N,-qK\CF$J$lg,"C?%3NdjNr
h!H7Flp-qn.K*1k HMM rQ$?|\lN#gl,d!Nv},s2ilk%^?$2 @l3<Q9+iPurjP9kj!Khklp-q

2M8%[1] j74R, g3I0, b\_(, B#_’l3<I1
jdjKX9k&fN]jH=u, ERpsL.Xq@8o, Vol.J88-D-I, No.2, pp.576-589(2005).
[2] #fX, Pn0i’;Q8qrP]H7?@l#G
ps!wN?aN#gl]u, psh}Xq@8o,
Vol.41, No.4, pp.1038-1045(2000).
[3] K#I’, YtK/, 7]N, >\5#: #t\YrQ$?2M8%N1j, psh}Xq&fqsp, DBS130, pp.181-188(2003).
[4] A. McCallum, K. Nigam, J. Rennie, and K. Seymore’Building Domain-specific Search Engines with Machine Learning Techniques,
AAAI Spring Symposium on Intelligent Agents inCyberspace(1999).
[5] 9x?, Tfal, pDw#, A5Sn’JX;Q@8=jNQB!#]u79F‘, psh}Xq@8o,Vol.23, No.2, pp.202-210(1982).
[6] fn5V, r\I4, 9$’’P=QYH"?QYKpE/lgQljP, +3@lh}, Vol.10, No.1,pp.27-45(2001).
[7] H. Nanba, T. Abekawa, M. Okumura, and S. Saito’
Bilingual PRESRI: Integration of Multiple
Research Paper Databases, In Proceedings ofRIAO 2004, pp.195-211(2004).
[8] 4#}K’@8=jr@$9(k, psh}Xq@8o, Vol.40, No.7, pp.2937-2945(1999).
[9] +}5R, qHQL, j71<’#gl]uKhk[@lG-R5l?qopsN1j, psJX;QU)<i‘ (FIT 2004).
[10] M. Tonoike, M. Kida, T. Takagi, Y. Sasaki,T. Utsuro, and S. Sato’Translation Estimation for Technical Terms using Corpus
collected from the Web, Proceedings of thePacific Association for Computational Linguistics(PACLING05), pp.325-331(2005).