You know how to toggle the display width function grad a: Well maybe she hadn't just started transcribing me yet .  , so we haven't had a meeting for a while , and and probably won't have one next week , I think a number of people are gone .  , so Robert , why don't you bring us up to date on where we are with EDU ? grad b:  in a in a smaller group we had  , talked and decided about continuation of the data collection . So Fey 's time with us is almost officially over , and she brought us some thirty subjects and , t collected the data , and ten dialogues have been transcribed and can be looked at . She 's actually suggested to look  , at the psychology department students , because they have to partake in two experiments in order to fulfill some requirements . And  , we want to design it so that they really have to think about having some time , two days , for example , to plan certain things and figure out which can be done at what time , and , sort of package the whole thing in a in a re in a few more complicated  , structure . As for SmartKom , I 'm the last SmartKom meeting I mentioned that we have some problems with the synthesis , which as of this morning should be resolved . grad b: " should be " means they aren't yet , but but I think I have the info now that I need . Plus , Johno and I are meeting tomorrow , so maybe   , when tomorrow is over , we 're done . And ha n hav we 'll never have to look at it again Maybe it 'll take some more time , to be realistic , but at least we 're we 're seeing the end of the tunnel there .  , the  ,  I don't think we need to discuss the formalism that 'll be done officially s once we 're done .  , something happened , in on Eva 's side with the PRM that we 're gonna look at today , and  , we have a visitor from Bruchsal from the International University . grad a: So when you said " Andreas " I thought you were talking about Stolcke . grad b: And , grad a: Now I know that we aren't , OK . grad b: Eh grad c: Cuz there is another Andreas around , grad a:  . grad b: So my scientific director of the EML is also the dean of the International University , one of his many occupations that just contributes to the fact that he is very occupied . And , the  , he @ @ might tell us a little bit about what he 's actually doing , and why it is s somewhat related , and by  using maybe some of the same technologies that we are using .  , so , I 've be just been looking at , Ack ! What are you doing ? Yeah .  , so , this is , sort of like the latest thing I have on it , and I sorta constructed a couple of classes . Like , a user class , a site class , and and you know , a time , a route , and then and a query class . And I tried to simplify it down a little bit , so that I can actually  , look at it more .  , so basically I took out a lot of stuff , a lot of the decision nodes , and then tried to The red lines on the , graph are the  , relations between the different  , classes . Like , a user has like , a query , and then , also has , you know  , reference slots to its preferences , the special needs and , you know , money , and the user interest . And so this is more or less similar to the flat Bayes - net that I have , you know , with the input nodes and all that . And So I tried to construct the dependency models , and a lot of these stuff I got from the flat Bayes - net , and what they depend on , and it turns out , you know , the CPT 's are really big , if I do that , so I tried to see how I can do ,  put in the computational nodes in between . And so I ended up making several classes Actually , you know , a class of with different attributes that are the intermediate nodes , and one of them is like , time affordability money affordability , site availability , and the travel compatibility . And so some of these classes are s some of these attributes only depend on stuff from , say , the user , or s f just from , I don't know , like the site . S like , these here , it 's only like , user , but , if you look at travel compatibility for each of these factors , you need to look at a pair of , you know , what the  , preference of the user is versus , you know , what type of an event it is , or you know , which form of transportation the user has and whether , you know , the onsite parking matters to the user , in that case . And that makes the scenario a little different in a PRM , because , then you have one - user objects and potentially you can have many different sites in in mind . And , they all depend on the same users , but different sites , and that makes a I 'm tr I w I wa have been trying to see whether the PRM would make it more efficient if we do inferencing like that . And so , I guess you end up having fewer number of nodes than in a flat Bayes - net , cuz otherwise you would c well , it 's probably the same . But  , No , you would definitely have be able to re - use , like , all the user stuff , and not not having to recompute a lot of the stuff , because it 's all from the user side . But , you know , in the case where , it depends on both the user and the site , then I 'm still having a hard time trying to see how  , using the PRM will help .  , so anyhow , using those intermediate nodes then , this this would be the class that represent the intermediate nodes . And that would basically it 's just another class in the model , with , you know , references to the user and the site and the time . And then , after you group them together this no the dependencies would of the queries would be reduced to this .  , so I think that 's about as far as I 've gone on the PRM stuff . And one is basically how desirable a site is meaning , how good it matches the needs of a user .  , so , instead of  , doing a lot of , you know , computation about , you know , which one site it wants of the user wants to visit , I 'll come well , try to come up with like , sort of a list of sites . And for each site , you know , where h how how well it fits , and basically a rating of how well it fits and what to do with it . She 's ac   Eva 's got a little write - up on it that  , probably gives the the details to anybody who needs them .  , so the You you didn't look at all yet to see if there 's anybody has a implementation . So one so one of the questions , you know , about these P R Ms is grad d:   professor f: we aren't gonna build our own interpreter , so if if we can't find one , then we  , go off and do something else and wait until s one appears .  , so one of the things that Eva 's gonna do over the next few weeks is see if we can track that down . If there is an interpreter , it looks like you know , what Eva 's got should run and we should be able to actually  , try to solve , you know , the problems , to actually take the data , and do it .  , I actually think it is cleaner , and the ability to instantiate , you know , instance of people and sites and stuff , will help in the expression . I think there are things that you can express this way which you can't express in a normal belief - net , without going to some incredible hacking of sort of rebuilding it on the fly .  , the notion of instantiating your el elements from the ontology and stuff fits this very nicely and doesn't fit very well into the extended belief - net . So , people who have thought about the problem , like Robert i it looked to me like if Eva were able to come up with a you know , value for each of a number of  , sites plus its EVA thing , that a travel planner should be able to take it from there . And you know , with some other information about how much time the person has and whatever , and then plan a route . grad b:  -  , well , first of all  , great looks , mu much cleaner , nnn , nnn , Certain certain beauty in it , so , if beauty is truth , then ,  we 're in good shape . So if you have a write - up then  , I 'd love to read it grad d:   grad b: and  because , i Can you go all the way back to the the very top ? grad d: Yeah . grad b:  these @ @ these w w when these are instantiated they take on the same values ? that we had before ? grad d: I can't really see the whole thing . grad b: or are they have they changed , in a sense ? grad d: Well I think I basically leave them to similar things . grad d: Some of the things might that might be different , maybe like are that the hours for the site . grad d: And , eventually I meant that to mean whether they 're open at this hour or not . grad d: And status would be , you know , more or less like , whether they 're under construction , and and or stuff like that . grad b: And the , other question I would have is that presumably , from the way the Stanford people talk about it , you can put the probabilities also on the relations . I don't remember whether they carried that over to this or not , grad a: Mmm . grad b: It 's sort of in the definition or in the in Daphne 's definition of a PRM is that classes and relations , professor f: OK . grad b: and you 're gonna have CPT 's over the classes and their relations . grad d: I remember them learning when , you know , you don't know the structure for sure , professor f: Yeah . grad d: but I don't remember reading how you specify grad b: Yeah , that would be exactly my question . So , the the plan is is when Daphne gets back , we 'll get in touch and supposedly , we 'll actually get s deep seriously connected to to their work and grad b: Yep . professor f: somebody 'll  , you know If it 's a group meeting once a week probably someone 'll go down and , whatever . We get rocking and rolling on this again , once we get a package , if , when , and how , then this becomes foregrounded grad d:   grad b: And  , until then we 'll come up with a something that 's @ @ that 's way more complicated for you . grad b: Because this was laughingly easy , right ? grad d: Actually I had to take out a lot of the complicated stuff , cuz I I made it really complicated in the beginning , and Jerry was like , " this is just too much " . So , you could , from this , go on and say suppose there 's a group of people traveling together and you wanted to plan something that somehow , with some Pareto optimal  , thing for grad a: That 's good . professor f: or grad a: Except for humans can't really solve it either , so . Well that 's the that would that would be a  , you could sell it , as a grad a: Yeah . professor f: OK , eh you don't have to fight about this , just give your preferences to the grad a: And then you can blame the computer . But what does it  Would a pote potential result be to to split up and never talk to each other again ? You know . So there i there are some some u  , you know , elaborations of this that you could try to put in to this structure , but I don't think it 's worth it now . But  , it 's good , yeah and and there were a couple other ideas of of  , things for Eva to look at in in the interim . So , I 'm not really involved in any project , that 's  that 's relevant to you  , a at the moment , the the reason is really for me  , to have an opportunity to talk to some other researchers in the field . And and so I 'll just n sort of give you a real quick introduction to what I 'm working on , and  , I just hope that you have some comments or , maybe you 're interested in it to find out more , and and so I 'll be  , happy to talk to you and and  , I 'd also like to find out some more and and maybe I 'll just walk around the office and and then and ask some some questions , in a couple days . OK , so , what I started looking at , to begin with is just  , content management systems  , i i in general . So  ,  what 's  Sort of the state of the art there is to   you have a bunch of of  documents or learning units or learning objects , and you store meta - data  , associate to them . So there 's some international standards like the I - triple - E ,  There 's an I - triple - E , LON standard , and  , these fields are pretty straightforward , you have  author information , you have  , size information , format information and so on . One is  you store keywords associated with the  with the document , and one is  , you have sort of a , well , what is the document about ? So it 's some sort of taxonomic  , ordering of of the of the units . Now , if you sort of put on your semantic glasses ,  you say , well that 's not all that easy , because there 's an implicit  , assumption behind that is that  , all the users of this system share the same interpretation of the keyword and the same interpretation of  , whichever taxonomy is used , and  , I think that 's a that 's a very that 's a key point of these systems and they sort of always brush over this real quickly without really elaborating much of that and  As a matter of fact , the only thing that m apparently really works out so far are library ordering codes , which are very , very coarse grain , so you have some like , science , biology , and then But that 's really all that we have at the moment . Now , what this  a standard like this would give us is we could  , sort of  with a search engine just query  , different repositories all over the world . But we can't really  , so what I 'm what I try to do is  , to have  ,  So . So the scenario is the following , you you 're working on some sort of project and you encounter a certain problem . Now , what what we have at our university quite a bit is that  , students  , try to u program a certain assignment , for example , they always run into the same problems , and they always come running to us , and they 'll say why 's it not it 's not working , and we always give out the same answer , so we thought , well , it 'd be nice to have a system that could sort of take care of this , and so , what I want to build is basically a a smart F A Q system . Now , what you  need to do here is you need to provide some context information which is more elaborate than " I 'm looking for this and this and this keyword . I 'm I 'm sure you have the same when when somebody utters a sentence in a certain , context it , and and the same sentence in another context makes a huge difference . So , I want to be able to model information like , so in the in the context of in the context of developing distributed systems , of a at a computer science school , what kind of software is the person using , which homework assignment is he or she working on at the moment , maybe what 's the background of that student 's  , which  , which error message was encountered . Now , basically giving this   so we somehow need to have a formalized  , way of writing this down basically , and that 's where the shared interpretation of of certain terms and keywords comes in again . And , using this and some some  , knowledge about the domain I think you can do some some simple inferences . Like you know that when somebody 's working about  , working on on servlets for example , he 's using Java , cuz servlets are used are written in Java . So some some inferences like that , now , u using this you can infer more information , and you could then match this to the meta - data of  off the documents you 're you 're searching against . So ,  what I wanna do is basically have some sort of  given these inputs , and then I can compute how many documents match , and use this as a metric in the search . Now , what I plan to do is I want to  sort of do a   try to improve the quality of the search results , and I want to do this by having a depth  ,  steepest descent approach . So if I knew which operating system the person was working on , would this improve my search result ? And and having  ,  a symbolic formalized model of this I could simply compute that , and find out which  which questions are worth  , asking . And that 's what I then propagate back to the user , and and sort of try to optimize the search in this way . Now , the big problem that I 'm facing right now is  , it 's fairly easy to hack up a system  quickly , that that works in the small domain , but the problem is obviously the scalability . And   , so Robert was mentioning  , earlier today is that  , Microsoft for example with their printer set up program has a Bayesian network , which does exactly this , but there you face a problem that these are very hard to extend . And so ,  what I 'm What I try to do is basically try to model this  , in a way that you could really combine  , knowledge from very different sources , and and  , sort of looking into some of the ideas that the semantic web community  , came up with . Trying to to have  , an approach how to integrate s  certain  representation of certain concepts and also some computational rules , what you can do with those . What I 'm also looking into is a probabilistic approach into this because document retrievals is a very fuzzy procedure , so it 's probably not that easy to simply have a symbolic  , computational model . And then  ,  sort of as an add - on to this whole idea ,  that would be now , depending on what the search engine or the content repository depending on which  , which  , rules and which ontologies it it uses , or basically its view of the world ,  you can get very different results . And there you could have an idea where you actually have sort of a a peer to peer approach , where we 're all sort of carrying around our individual bookshelves , and  , if you have a question about a homework , it 's probably makes sense to ask somebody who 's in your class with you , sort of the guru in the certain area , rather than going to some Yahoo - like  , search engine . And I think a lot of the even though it 's a it 's a very different domain , but I think a lot of the , issues are are fairly similar . grad a: And so some of the I don't know how much you know about the larger Heidelberg project , I Are you grad c:  I know , yeah I know abou about it . It 's like , you know , the c context - based factors that influence how you interpret , grad c:   We - we 've kind of talked about that , but we haven't worried too much about that end of the discourse . grad b: Well , in a in one t one s mmm , small difference in a in a way , is that he doesn't have to come up with an answer , but he wants to point to the places w w grad a: Documents that have the answers . So I 'm I 'm not I 'm not building an expert grad a: you have to s still m understand what the content says about itself , and then match it to what you think the informational needs grad a:   You 're just taking the keywords as a topic text , as grad c: I I assume that that the there will be learning systems that that tag their their content . grad c: And  , m @ @ and basically what I what I envision is that you rather than just supplying a bunch of keywords you could basically for for an FAQ for example you could state sort of like a logic condition , when this document applies . So " this document explains how to set up your  , mail account on Linux " or something like this . So something something very specific that you can then But the I think that the key point with these  , learning systems is that  , a learning system is only as good as  the amount of content it it carries . grad c: You can have the best learning system with the best search interface , if there 's no content inside of it , it 's not very useful . So I think ultimately because  ,  developing these these rules and these inference  inferences I think is very costly , so  ,  I think you must be able to reuse some some existing  , domain domain information , or or or ontologies that that  other people wrote and then try to integrate them , and then also search the entire web basically , rather than just the small  , content management system . grad c: So I think that 's that 's crucial for for the success of or @ @ grad a: So , you 're not I guess I 'm trying to figure out how how it maps to the kinds of things that we 've talked about in this group , and , actually associated groups , grad c:   grad a: cuz some of us do pretty detailed linguistic analyses , and I 'm guessing that you you won't be doing that ? OK . grad a: So , you take the query , and and professor f: On the other hand , FrameNet could well be useful . professor f: Because , you know , the standard story is that keyworks keywords evoke frames , and the frames may well give you additional keywords or  , if you know that that that a a bunch of keywords  , indicate a frame , then you can find documents that actually have the whole frame , rather th than just  , individual grad c: Mmm . There 's linguists and stuff and there 's a lot of it and they 're they 're busily working away . And this looks t it seems to be that this is a place where you might be able to do that . I 'm sure I could learn a lot about  , yeah , just how to how to come up with these structures , grad a: Mmm . grad c: cuz it 's it 's very easy to whip up something quickly , but it maybe then makes sense to to me , but not to anybody else , and and if we want to share and integrate things , they must well , they must be well designed really . grad b: And Andreas and I tried to come up wi or we had come up actually with a eh with him working on an interface for FrameNet , as it was back then , that would p do some of the work for this machine , professor f: Right . grad b: which  , never got done because Prashant found a happy occupation professor f: W yeah , I know ,  it it he w he did w what what he did was much more s sensible for him . professor f: I think  , grad b: But so I 'm just saying , the  , we had that idea professor f: you know Yeah . professor f: Yeah , actually you guys never grad b: And Srini 's doing information extraction also , right ? professor f: Right . grad c: professor f: this was supposedly an exchange program , and I we you know , it 's fine . We don't care , but it just I 'm a little surprised that  , Andreas didn't come up with anyone else he wanted to send .  I had forgotten a I To be honest with you , I 'd totally forgotten we had a program . grad b:  it 's in the program ? grad c:  I I think it 's it 's really the lack of students  , at IU at the moment . I think it 's ju it 's more the lack of of students , really , and w we have all these sponsors that are always sort of eager to get some teams . grad c: Well  if if I were a student , I 'd love to come here , rather than work for some German company , or professor f: Yeah . professor f: Oh , right ! grad c: Well , I didn't say anybody to anything to offend well , except for the sponsors maybe , but professor f: Right . So I thi tha that 's that 's one of the things that might be worth looking into while you 're here . professor f: unfortunately , Srini , who is heavily involved in DAML and all this sort of stuff is himself out of town . professor f: I don't know why he @ @ oh , I , who knows ? grad a: The  professor f: Anyway , s yeah , you 'll see you 'll certainly see a lot of the people there . grad a: The other person I thought of is Dan Gildea ? because he did some work on topic spotting professor f: Yeah . I don't Depending on how well you wanna integrate with that end , grad c:   grad a: you know , like , taking the data and fig you said the learning systems that figure out We There 's someone in ICSI who actually has been working on has worked on that kinda stuff , and he 's worked with frame net , so you could talk to him about , you know , both of those things at once . grad c: So , who is that again ? grad a: And , he 's in one of the rooms on the fifth floor and stuff , grad b: Who ? I can take you to his office . professor f: Alright , was there anything else for this ? One of these times soon we 're gonna hear about construal . professor f: Good thinking ! grad b:  well , maybe I can I can bribe my way out of this . professor f: Well , no , but he 's he 's he 's he 's as you said , he 's , like the state legislature , he 's trying to offer us bribes . grad b: This  Oh , they refused the budget again ? Is it so about CITRIS ? Yeah , still nothing . professor f: this this this t the s we 're , involved in a literally three hundred million dollar  , program . And , the State of California is now a month and a half behind its legis its legally required date to approve a budget . professor f: and , yesterdayday there was this   I thought that the other branch would just approve it , but now there 's actually a little back sliding to people who who approved it got flak from there , eh anyway . So ,  Oh ! I have to tell you a wonderful story about this , OK ? And then we 'll go . In fact he 's hired to run a lot of CITRIS , even though we don't have the money they So they 've been hiring people right and left , so , they think the money 's coming . And , is now doing all the politics for CITRIS , but also , has a  , a lot of interest in  , actually doing things for society , so digital divide and stuff like that . But the really interesting thing was , he st he s he s said something about , you know I 'm interested in things that have high social multiplier , something that is of great social value . He said , " for example " , this was his only example , " if you had a adult literacy program that was as good as an individual tutor , and as compelling as a video game , then that would have a huge social impact " . So it was nice that  , he 's got this view , of A , that 's what you should try to do , and B , language would be a good way to do it . I didn't push him on the ch on the child thing , grad a:  - huh . professor f: but , you know , a again , if if you if you grad a: Oh . So this is reading , rather than teaching Another project we started on , and and didn't get funded for was , to try to build an automatic tutoring program , for kids whose first language wasn't English . So , enormous problem in California , and the idea was if we 're so smart about language understanding and speech understanding , couldn't we build  , programs that would be tutors for the kids . professor f: and  , I know none of us have the spare time to look at it right now , but it i it 's it 's interesting and I may  , talk to him some more about is em somebody already doing this , and stuff like that . So I I did manage to get pull my head out of the sling by sidetracking into CITRIS , professor f: No , no . grad b: but , I I 'll volunteer to put it right back in by stating that I am n  among some other things in the process of writing up stuff that we have been discussing at our daily meetings , professor f: Yeah . grad b: and also revising , thanks for all the comments , the c the original construal proposal . And , if I put one and one together , I may end up with a number that 's greater than one and that I I can potentially present once you get back . Yeah , so OK , so that 'd be great , but I 'd I think it 's it 's time again , right ? grad b: Absolutely . grad b: But  , and hopefully all sidetracking  , other things will have disappeared , soon