Recovering Problem-Solving Activities from Query Messages Yoshihiko H A Y A S H I N T T I n f o r m a t i o n and C o m m u n i c a t i o n Systems Laboratories 1-2356 T a k e , Y o k o s u k a , 238-03 J A P A N E-mail:
[email protected]
Abstract We investigated a set of query messages taken f r o m an Usenet newsgroup, and analyzed relations between t h e nature of problem-solving act i v i t i e s and their n a t u r a l language descriptions. Based on the corpus investigation, this paper proposes an efficient c o m p u t a t i o n a l mechanism for recovering problem-solving activities f r o m query messages w r i t t e n in Japanese. T h e m a i n c l a i m of the paper is t h a t the u n d e r l y i n g p r o b l e m - s o l v i n g a c t i v i t y described in a n a t u r a l language message can be efficiently recovered if p r o v i d e d w i t h general knowledge on h u m a n problem-solving and the associated linguistic p a t t e r n s in the descriptions.
1
Introduction
In this paper, we focus on trouble-shooting type problem-solving activities. One general way to solve such a complex p r o b l e m is to k n o w a solution which m i g h t solve the p r o b l e m and to apply i t . These days some people utilize c o m p u t e r networks as a f o r u m useful for p r o b l c m - s o l v i n g [ l l a m m o n d , 1995]. T h u s understanding how people ask for i n f o r m a t i o n w i t h electronic messages w i l l be inevitable to realize an intelligent i n f o r m a t i o n access f u n c t i o n on i n f o r m a t i o n super highways. W i t h this m o t i v a t i o n , we started this work w i t h an investigation of a set. of actual query messages, which had been taken f r o m an Usenet n e w s g r o u p [ K r o l , 1993]. T h e newsgroup chosen as our corpus is "fj.sys.mac" 1 , which provides a f o r u m of discussions about Apple's Macintoshes, m a i n l y for Japanese-speaking people. We selected f o r t y - t w o messages, aimed at trouble-shooting, o u t of 119 query messages which appeared in a threem o n t h s ' t e r m in 1993. Each of these selected messages contains a description of the w r i t e r ' s trouble-shooting t y p e problem-solving a c t i v i t y .
2
A
Motivational
Example
Let us s t a r t w i t h a translated and slightly simplified example of an actual query message taken f r o m the corpus. 1
Needless to say, there are no particular intentions for the choice.
(Example) S1: I found my Mac II had been i n f e c t e d w i t h some k i n d of v i r u s . s 2 : So, I wanted to run a v a c c i n e program and s3: t r i e d to make my Mac read an MS-DOS f o r m a t t e d 2DD f l o p p y d i s k . s4: However, Apple F i l e Exchanger could not read i t . s5: C a n ' t MacIIs read MS-DOS f o r m a t t e d 2DDs? T h e story begins w i t h h i s / h e r discovery of a trouble ( s i ) and ends w i t h a query (s5). Sentences s2 t h r o u g h s4 describe his/her t r o u b l e - s h o o t i n g type problem-solving a c t i v i t y . How can people read this message? F r o m s2, we w i l l be able to guess t h a t , at least for h i m / h e r , r u n n i n g a vaccine p r o g r a m is a way to solve the trouble stated in s i . T h a n k s to the marker "so" in s2, we w i l l be able to guess t h i s , even if we do not have good knowledge about disinfecting computer viruses. On the other h a n d , the relation between s2 and s3 seems to be unclear on t w o p o i n t s . F i r s t , because the t w o sentences are connected by the c o n j u n c t i o n " a n d " , there are t w o possibilities for i n t e r p r e t i n g the role of the action described in s3; t h a t is, either running a. vaccine program followed by making Mac read a 2DD disk will shoot the trouble, or to run a vaccine program, making Mac read a 2DD disk is necessary. M a i n verbs in b o t h sentences may provide a slight clue. However, it does not seem to be a strong one. T h e d o m a i n knowledge, in general, m i g h t help the disambiguation process. However, if his/her actions were based on h i s / h e r w r o n g belief or knowledge, even correct d o m a i n knowledge w o u l d n o t be of h e l p 2 . In either case, it is clearly shown by S4 t h a t h i s / h e r t r i a l to make Mac read a 2 D D disk failed and this suggests t h a t he/she s t i l l cannot disinfect the virus f r o m his/her MacII. Note t h a t the entire problem-solving process described in the message can be seen as a goal-directed activity. T h e trouble stated i n s i may prevent h i m / h e r f r o m achieving h i s / h e r p r i m a r y goal, w h i c h is not explicit in the message. Therefore he/she introduces a new goal, disinfecting the v i r u s . T h e activities described in s2 t h r o u g h s4 are associated w i t h the new goal. In addi2
In this example, his/her doing s3 is actually underivable from correct domain knowledge. Most of the response messages to this query have pointed it out.
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tion, the query stated by s5 can be seen as a step of the problem-solving, although the level differs from the actual activities.
G. Enable link is used in cases where X is the only action to enable the goal. A-step link encodes the action X is one of the decomposed action to achieve the goal G. Generate link is used in cases where X is the only decomposed action. Not-executable encodes the problem P prevents execution of the action X.
3 A Recovery Mechanism 3.1 Overview Our recovery mechanism consists of three cascaded processes. The first process identifies message fragments, each of which describes a single problem-solving step of the entire activity, by recognizing some distinctive surface expression patterns, as in many information extraction systems[Hobbs, 1992],[Kitani, 1994], Each fragment is then assigned a sub-graph which represents the structure of the step by the second process. The third process finally integrates these sub-graphs and represents the entire problem-solving activity as a set of graph structures with help from general knowledge on problem-solving and the associated linguistic heuristics in the discourse structures. Each of the graphs represents a possible underlying problem-solving activity. We call such a graph problem-solving graph, or PS-graph in short. 3.2 Ontology for the PS graphs In this paper, we assume that a goal state is enabled by one of the alternative goal-achieving actions, and a goal-achieving action is generated by a sequence of decomposed actions.
• Causality type: Caused link encodes the action X caused the problem P. Cause-always link is used when the agent knows a fact that X always causes P which may be an undesirable side-effect. • Problem-solving type: To-solve link encodes the agent has a new goal state G in which the problem P does not come about. It is automatically introduced whenever the agent knows a problem came about. • Auxiliary type: Similar link connects two same/similar problematic states. It is typically used in cases where the same problem comes about again, in spite of the fact that a problem-solving activity has been conducted. 4
Recovery of Single PS Step
4.1 Types of problems We looked through the forty-two objective messages and extracted sixty-three problem description fragments. Table 2 classifies types of the problems. The classification was conducted by focusing on following three points: 1. Did he intend to do some action? 2. Did he actually do the action? 3. Is there a problematic situation /si now? In the table, example expressions in English and the number of occurrences for each type are also shown. Here, we distinguished two situations: • Fl (primary): The problem is introduced as a primary problem for the writer. Because most of the problem-solving activities are described in chronological order, it appears prior to the other levels of problems in the descriptions.
There are four node types for the PS-graphs; • G node: It encodes a goal state of the agent (writer), and may have its value, achieved/unachieved. • P node: It encodes that a problematic situation (a trouble) came about, and may have its value, fixed/unfixed. • X node: It encodes an action by the agent, and may have its value, succeeded/failed. • XP node: It is a composite node by an X node and a P node connected by a causality type link. It encodes a causal relation, an action caused a trouble. We have ten direct link types as shown in Table 1. • Action type: alternative link encodes the action X is one of the alternative actions which enables the goal
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• F2 (lower-level): The problem came about during the problem-solving activities. It mainly describes a situation where the writer's goal-achieving or problem-solving activity caused the same problem or introduced a new problem. Note that we included the problem type (f) in our variety of problem types. In this type, actually, there is no trouble anymore. For the example in the table, the writer fixed the problem (the print process doesn't terminate) by an action (send Ctrl-d to the printer). However, we can imagine that he/she is not convinced by the solution, and wants to know a better solution. We see human problem-solving in a broader sense than usual. 4.2 Identifying problem descriptions Table 3 lists expression patterns which can be used for the identification of problem descriptions. By these patterns, 92.1% (58/63) of the problem descriptions in the
corpus are covered. P a r t i c u l a r m o d a l expressions in T y p e - A p r o v i d e the strongest clues; and these are closed expressions. Here we w o u l d like to remark on t w o m a j o r m o d a l expressions w h i c h strongly suggest t h a t t h e associated propositional p a r t of a description describes a p r o b l e m atic s i t u a t i o n . • verb + " t e - s h i m a u " : T h i s expression's original funct i o n is to represent the perfect tense. However in m a n y cases, it represents a nuance t h a t the w r i t e r t h i n k s / f e e l s t h a t the s i t u a t i o n described by the main-clause is undesirable for h i m / h e r [Masuoka, 1989]. In this d o m a i n , it t u r n s o u t to be describing a problematic situation. • verb + " t e - k u r e - n a i " : T h i s is a negation f o r m of " t e - k u r e r u " , w h i c h represents a s i t u a t i o n where the agent of the verb is not the w r i t e r and the associated s i t u a t i o n is desirable (empathy in [ K u n o , 1987]) for h i m / h e r . Therefore, in this d o m a i n , its negat i o n f o r m , " t e - k u r e - n a i " , represents t h a t the w r i t e r t h i n k s the s i t u a t i o n caused by a systems/program's behavior is p r o b l e m a t i c . In contrast to these expressions, other T y p e s are open expressions. T h u s , we must prepare a set of explicit p a t t e r n s w h i c h covers possible expressions in advance. 4.3
Recognizing problem type
T h e p r o b l e m types (b) t h r o u g h ( f ) , shown in Table 2, are expressed m a i n l y by c o n d i t i o n a l clauses/sentences. Table 4 lists c o m b i n a t i o n s of expression p a t t e r n s by which we can m a p an identified p r o b l e m description i n t o one of the p r o b l e m types. In the table, we indicate the patterns
as a t r i p l e , x - p a r t , connective, and y - p a r t ; here, x - p a r t is the antecedent and y - p a r t is t h e consequent of a cond i t i o n a l expression. T h e following are brief explanations a b o u t the d i s t i n c t i v e Japanese connectives which appear in the table w i t h respect to the p r o b l e m types. •
" - b a a i " (= in case of - i n g ) : Use of t h i s connective suggests t h a t the c o n d i t i o n a l sentence describes a k i n d of fact. T h u s , it insists t h a t the p r o b l e m t y p e may be ( b ) , in w h i c h an undesirable side-effect caused by an action is described.
•
"-nodesuga" : T h i s connective establishes the antecedent ( x - p a r t ) as a background description. Use of this connective, together w i t h an i n t e n t i o n a l expression in t h e x - p a r t , suggests to us t h a t one of the pre-conditions for the intended action d i d not hold at the t i m e .
•
" - t o " (= i f / w h e n ) : T h i s connective is the most common and n e u t r a l one. It corresponds to "if* or " w h e n " in English.
•
" - n o n i / n i m o kakawarazu" (= even i f ) : These connectives m i g h t be similar to "even if'' or " a l t h o u g h " in English. As [Masuoka, 1989] discusses, these connectives emphasize t h a t there is an expectation v i o l a t i o n for the speaker. Therefore, this type is strongly connected w i t h t h e p r o b l e m t y p e (d2) and (e).
We confirmed t h a t the m a p p i n g rule gave us a fairly accurate result (average-recall: 73.0%, average-precision: 90.2%) t o w a r d t h e corpus d a t a by a hand s i m u l a t i o n . As the result shows, in the c u r r e n t m a p p i n g rule, stress is placed on the precision rate.
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4.4
Assigning a sub-graph
• type (e): [ A l l e n , 1984] i n t r o d u c e d a predicate NOTT0-D0(a,t,p) it w o u l d be t r u e if t h e p l a n p i n cludes n o t p e r f o r m i n g the action a at the t i m e t. Like this t r e a t m e n t , we regard not p e r f o r m i n g the action X i n t e n t i o n a l l y as a k i n d of a c t i o n . Therefore, we link the X' and the P node by the caused l i n k . We can imagine, in this case, t h a t the w r i t e r is wondering why the solution d i d n ' t w o r k . T h e new goal G, thus, w o u l d be to k n o w the reasons, and the associated i n f o r m a t i o n request m a y be described in the query message.
By the second process of the mechanism, each of the extracted fragments is then assigned one of the ready-made sub-graphs shown in Figure 1 according to its p r o b l e m type. Each s i t u a t i o n and the associated newly i n t r o duced goal G can be described as follows: • type (a): He/she has a new goal state G in which the p r o b l e m encoded in P is fixed. • type ( b ) : He/she knows t h a t there is an undesirable side-effect represented by P. T h e new goal G is either, execute X w i t h o u t P, or simply solve P.
• type ( f ) : As m e n t i o n e d in 4 . 1 , the sub-graph encodes an extended p r o b l e m - s o l v i n g a c t i v i t y . T h e newly i n t r o d u c e d goal G w o u l d be to k n o w a better solution to solve the once solved p r o b l e m P. T h a t is, the G w o u l d be strongly associated w i t h an i n f o r m a t i o n request in the query message.
• t y p e (c): He/she knows t h a t one of the preconditions for executing X d i d not hold. Hence, he/she believes t h a t X is not executable. To make hold t h e condition and make X be executable is the new goal. • t y p e ( d l ) : He/she knows t h a t the action X caused a problematic s i t u a t i o n P, and has a goal to solve i t . T h e p r o b l e m P w o u l d prevent achievement of upper-level goals. • t y p e ( d 2 ) : He/she knows t h a t the action X, i n tended to solve an upper-level p r o b l e m , caused same p r o b l e m P again; and he/she has a new goal to solve
it.
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5 5.1
Recovery of an E n t i r e PS A c t i v i t y Overall algorithm
Figure 2 outlines the overall a l g o r i t h m . T h e i n p u t to the a l g o r i t h m is a set of sub-graphs p r o v i d e d by the second process. As far as we looked t h r o u g h the set of messages, most of t h e problem-solving activities are described in chronological order. T h u s , the a l g o r i t h m basically iter-
ates t h r o u g h the each sub-graph in the i n p u t set, and constructs a set of possible PS-graphs incrementally 3 . 5.2
Linking sub-graphs
T h e Base-line T h e central p a r t of the a l g o r i t h m links a current subgraph (c-graph in the a l g o r i t h m ) i n t o a PS-graph bei n g c o n s t r u c t e d . T h e procedure, make-graph-1, does the j o b . T h e crucial p o i n t here is which node in the c-graph should be connected to w h i c h node in the being constructed PS-graph by which t y p e of link. T h e answer to the first p o i n t is provided by the procedure, get-top-node. It simply returns the t o p node in the c-graph as one p a r t of the connection p o i n t . Note t h a t we can n a t u r a l l y expect t h a t the returned node is l i m i t e d to the action t y p e (X node). As indicated in Figure 1, all the top nodes are X nodes, except for problem type (a) and ( f ) . Because the problem type (a) only appears in the b e g i n n i n g of descriptions, we d o n ' t have to worry about this. In a d d i t i o n , the problem type ( f ) can be seen as an extension to the main problem-solving act i v i t y ; the t o p P node would be simply linked to another P node by a similar link 4 . T h e answer to the second p o i n t is given by the procedure, get-link-points. G i v e n a PS-graph being cons t r u c t e d , it returns possible nodes in the PS-graph which can be linked t o . A c c o r d i n g to the graph ontology i n t r o duced by Table 1, G nodes, X nodes and P nodes would be the candidates. However, we can exclude P nodes, as these are provided only by the i n p u t to the a l g o r i t h m . T h e y are already p o i n t e d by X nodes, or they are t o p level nodes. T h e answer to the t h i r d point is provided by the procedure, check-linkable. Given a pair of nodes w h i c h consists a connection p o i n t , it returns a type of link to be used. Based on the discussion so far, a possible pair { P S graph-node, c-graph-nodo} is either {G node, X node} or {X node, X n o d e } . As enable/generate links are special cases of a l t e r n a t i v e / a - s t c p links respectively, the procedure returns alternative for the first pair, and a-step for the second pair. Constraints and heuristics for reducing the candidates T h e get-link-points m a y r e t u r n more t h a n one node in a PS-graph being constructed as a candidate of the l i n k i n g points. As this nature is a source of the ambiguities in PS-graphs, it is i m p o r t a n t to reduce the number of the candidates to avoid the c o m b i n a t o r i a l explosion. We can u t i l i z e some constraints to exclude i n a p p r o priate candidates. F i r s t , we cannot select the X nodes w h i c h are already m a r k e d failed as a candidate: the agent cannot p e r f o r m any action in order to p e r f o r m an already failed a c t i o n . Second, we cannot choose the G nodes w h i c h are already m a r k e d achieved as a candidate. Such G nodes are possible, if the ( f ) t y p e sub-graph has already been i n t r o d u c e d to the PS-graph. These cons t r a i n t s seem to n a t u r a l l y come f r o m general schema of s
For the explanation, the algorithm is slightly simplified. There would be several ways to optimize it. We simply ignore this case in the rest of the paper.
h u m a n problem-solving activities. T h i r d , as a PS-graph is constructed as t o p - d o w n and l e f t - t o - r i g h t w i t h t i m e , we can use this constraint to reduce the candidates. F u r t h e r m o r e , we can introduce some heuristics to prune unlikely candidates. T h e f o l l o w i n g are principles 5 which also come f r o m general schema of h u m a n goalachieving activities: • Principle of alternative actions: Suppose X\ t h r o u g h X n are a l t e r n a t i v e actions to enable a goal G, and are sorted by goodness of the actions. It is n a t u r a l to assume t h a t the agent w i l l t r y to p e r f o r m A' I + 1 only w h e n he/she failed to p e r f o r m A",-. • Principle of decomposed actions: Suppose A ' i t h r o u g h X n f o r m a sequence of the decomposed actions to generate an action X. It is n a t u r a l to assume t h a t the agent w o n ' t t r y to p e r f o r m X i + 1 if he/she failed to p e r f o r m Xt. W i t h these principles, the associated heuristics can be summarized as follows: In a s i t u a t i o n like Figure 3(a), l i n k i n g the c-graph to G is allowed o n l y when the Xi is already marked failed. T h a t is, failure of X{ must be represented in the description. T h e G nodes w h i c h v i o late this cannot be the candidates. On the other h a n d , if there is a parallel relation in the associated discourse s t r u c t u r e , the Unking is strongly preferred. In a s i t u a t i o n like Figure 3 ( b ) , l i n k i n g the c-graph to X'o is allowed only when the X i is not already marked failed. T h e X nodes w h i c h violate this cannot be the 6
Of course, these principles are too strong. However, we confirmed that most of the messages follow these principles.
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candidates. On the other hand, if there is a temporal/sequential relation in the associated discourse structure, the linking is strongly preferred. L i n k i n g sub-graphs actually Given a PS-graph being constructed, a linkable node in the PS-graph, a c-graph and a possible link type, the procedure link-graphs actually links the c-graph into the PS-graph. Figure 3 has already shown how the linking would be done. However, note that when a c-graph is linked to a G node in a PS-graph, another graph, as shown in Figure 4, must be generated. As mentioned in 3.2, we assume that a goal state is enabled by one of the alternative goalenabling actions, not directly by a sequence of decomposed actions. B u t , these goal-enabling actions are often missed in the natural language descriptions. Therefore, to handle such a case, we must assume the existence of a virtual goal-enabling action and incorporate it in the PS-graph. We call such a virtual goal-enabling action virtual action, and denote it as X? in the PS-graphs. 5.3
Post-process
The following are conducted as post-process. Reducing redundant PS-graphs (reduce-graphs): As enable/generate links are special cases of alternative/astep links, this process first checks the alternative/a-step links that do not have sister links and changes them to enable/generate links. As often redundant PS-graphs are constructed due to the virtual action nodes, the procedure next checks redundant graphs, and preserves the most simple ones only. Assigning success/failure values to nodes (assignvalues): Based on the principles of alternative actions and decomposed actions, we can assign succeeded/failed to action nodes, achieved/unachieved to G nodes and fixed/unfixed to P nodes in a PS-graph, by propagating
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the i n p u t , SG3, to b o t h SG4 and SG5 in the next itera t i o n . In SG4, GO and XO are possible l i n k i n g points, b u t o n l y one g r a p h , SG6, result (shown in (c)). SG7 and SG8 are excluded by the heuristic based on the principle of a l t e r n a t i v e actions. On the other h a n d , in SG5, X? and XO are possible l i n k i n g p o i n t s , and SG9 and SG10 result (shown in ( d ) ) . Post process: T h r e e graphs, SG6, SG9 and SG10 are passed to the post process. By the procedure reducegraphs, SG9 is identified as a r e d u n d a n t variant of SG10; therefore, it is t h r o w n away. T w o graphs, SG6 1 and SG10' are finally p r o v i d e d as possible PS-graphs (shown in (e)). Note t h a t the ambiguous relationship between s2 ( " r u n vaccine") and s3 ("make Mac read a 2 D D disk 1 ') is clearly captured by these two PS-graphs. Also, we k n o w t h a t the p r i m a r y problem ("infected w i t h virus 1 ') is s t i l l unfixed in either case f r o m t h e PS-graphs.
6
Discussion
Clearly, the w o r k r e p o r t e d here has a close relation to the so-called plan recognition. Therefore, it may be w o r t h m e n t i o n i n g our view on the relation here. Roughly speaking, plan recognition in n a t u r a l language unders t a n d i n g has long been studied f r o m the perspective of for hearer, understanding the speaker's utterance is recognizing the speaker's plan which generates the utterance, and it is assumed t h a t the hearer and the speaker have same plan library. T h i s assumption seems to be too s t r o n g to handle act u a l h u m a n dialogues/messages. For one t h i n g , a plan which is valid for the speaker can be invalid for the hearer. T h u s , we cannot assume it in a c t u a l i t y . One of t h e i m p o r t a n t works which addressed the issue w o u l d be [Pollack, 1990]. In the paper, Pollack views plans as complex m e n t a l a t t i t u d e s and discusses how a speaker's invalid plans can be handled in dialogue understanding. O u r w o r k reported here was p a r t l y inspired by t h a t w o r k . However, as Woods points o u t in his comment[\Voods, 1990] to Pollack, she does not deal w i t h p a r t i a l l y specified plans. As shown in this paper, one can have an incomplete plan in a problem-solving a c t i v i t y . For example, one m i g h t plan to r u n a vaccine program in order to disinfect a computer virus w i t h o u t k n o w i n g the actual vaccine p r o g r a m . O u r n o t i o n of the recovery of p r o b l e m - s o l v i n g activities can include such cases; incomplete plan or p r e c o n d i t i o n failure in the plan recognition enterprise are handled themselves as one of the p r o b l e m atic s i t u a t i o n s . Besides t h i s , W o o d s made another i m p o r t a n t comment in his essay. He questions the role of surface expressions by i n t r o d u c i n g an example; "I want to get tenure, so I've rented a c a r " . He says, " t h e c o n j u n c t i o n so u n a m biguously signals t h e i n t e n d e d goal-achieving relationship w i t h o u t the necessity of d e t e r m i n i n g the plan in order to infer i t " . T h i s paper may provide an answer to this question, as we discussed p a r t i c u l a r l y w i t h the example.
7
Conclusions and Future Works
T h i s paper proposed an efficient c o m p u t a t i o n a l mechanism for recovering problem-solving activities f r o m query messages w i t h o u t p a r t i c u l a r d o m a i n knowledge. T h i s w o r k , however, may be a first t r i a l , and there remain several issues to be worked o u t . F r o m a c o m p u t a t i o n a l v i e w p o i n t , we must first evaluate t h e actual performance of the mechanism t h r o u g h i m p l e m e n t a t i o n and experiments w i t h a larger set of u n seen d a t a . On the other h a n d , f r o m a theoretical viewp o i n t , there are a number of harder issues. P a r t i c u l a r l y , our m a i n concern at t h e m o m e n t is the f o r m a l i z a t i o n of h u m a n problem-solving ( t r o u b l e - s h o o t i n g ) activities in terms of m e n t a l processes, as [Pollack, 1990] formalizes simple plans as complex m e n t a l a t t i t u d e s .
Acknowledgments 1 w o u l d like to t h a n k Jerry Hobbs for his valuable advice on this w o r k , and T s u n e a k i K a t o for his useful comments on an earlier version of this paper. T h e w o r k was done m a i n l y while I was s t a y i n g at C S L I , Stanford University. T h u s , thanks also go to people at C S L I and N T T .
References [ A l l e n , 1984] A l l e n , J. Towards a general theory of action and t i m e Artificial Intelligence 23, 123-154, 1984. [ H a m m o n d , 1995] H a m m o n d , K . R . , B u r k e , R.C., Mart i n , C, and L y t i n e n , S. F A Q Finder: A Case-based A p p r o a c h to Knowledge N a v i g a t i o n . In Proceedings of the 11th Conference on Artificial Intelligence for Applications, 80-86, Los Angels, C A , 1995. [Hobbs, 1992] Hobbs, J.R., A p p e l t , D.E., Bear, J.S., Israel, D.J., and T y s o n , W . M , F A S T U S : A syst e m for e x t r a c t i n g i n f o r m a t i o n f r o m natural-language t e x t . Technical Note No.519, S R I I n t e r n a t i o n a l , Menlo Park, C A , 1992. [ K i t a n i , 1994] K i t a n i , T . , E r i g u c h i , Y . , and H a r a , M . P a t t e r n m a t c h i n g and discourse processing in inform a t i o n e x t r a c t i o n f r o m Japanese t e x t . Journal of Artificial Intelligence Research, 2, 89-110, 1994. [ K r o l , 1993] K r o l , E. The Whole Internet, User's Guide & Catalog. O'R.eilly & Associates, Sebastopol, C A , 1993. [ K u u o , 1987] K u n o , S. Discourse and Empathy. O H , 1987.
Functional Syntax: Anaphora, U n i v e r s i t y of Chicago Press,
[Masuoka, 1989] Masuoka, T . , and T a k u b o , Y, Kiso Nihongo Bunpou. "Basic Japanese G r a m m a r " (in Japanese), K u r o s h i o - S h u p p a n , T o k y o , J a p a n , 1989. [Pollack, 1990] Pollack, M . E . Plans as complex mental a t t i t u d e s , in C o h e n , M o r g a n and Pollack (Eds.). Intentions in Communication. T h e M I T Press, C a m bridge, M A , 1990. [Woods, 1990] Woods, W . A . On plans and plan recognit i o n : C o m m e n t s on Pollack and on K a u t z , in Cohen, M o r g a n and Pollack (Eds.). Intentions in Communication. T h e M I T Press, C a m b r i d g e , M A , 1990.
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