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Scotland: KRAQ'05: Knowledge and Reasoning for Answering Questions -- CFP for a workshop at IJCAI'05

IJCAI Workshop, Edinburgh, July 30th, 2005


The introduction of reasoning capabilities in question-answering (QA) systems appeared 
in the late 70s. A second generation of QA systems, aimed at being cooperative, emerged 
in the late 80s - early 90s. In these systems, quite advanced reasoning models were 
developed on closed domains to go beyond the production of direct responses to a query, 
in particular when the query has no response or when it contains misconceptions. 
More recently, systems such as JAVELIN, Inference WEB or Cogex, operating over open 
domains, integrate gradually inferential components, but not as advanced as those of 
the 90s. Performances of these systems in the recent TREC-QA tracks show that reasoning 
components do improve the response relevance and accuracy. They can also potentially be 
much more cooperative. However, there is still a long way before being able to produce 
accurate, cooperative and robust QA systems. 

Recent foundational, methodological and technological developments in knowledge representation 
(e.g. ontologies, knowledge bases incorporating various forms of incompleteness or uncertainty), 
advanced reasoning forms (e.g. relaxation, intensional calculus, data fusion), not necessarily 
based on unification, advanced language processing resources and techniques (for question 
processing as well as for generating responses), and recent progress in HLT make it possible 
to foresee the elaboration of much more accurate, cooperative and robust systems dedicated 
to answering questions from textual data, from e.g. online texts or web pages, operating 
either on open or closed domains. 

The workshop will be organized around a few major questions of interest to a number of AI, 
NLP, HLT and pragmatics people. One main question is the characterization of those reasoning 
procedures that need to be developed to answer questions, either on closed or on open 
domains. Then, are enhancing reasoning procedures and accuracy of knowledge representation 
sufficient conditions to improve responses ? If not, what is the role of language processing 
and what are the relevant paradigms (e.g. lexical inference) ? How do language and reasoning 
interact ? Next, what are the language models and techniques appropriate for producing 
responses which sound natural for the user (relevant, fluid, of an appropriate granularity, 
with terms the user understands, etc.). Another perspective is the role of pragmatics as a 
means, for example, to better capture the user's goals and intentions from his query, and 
therefore to better organize the response. Pragmatics is also of importance to better 
analyse the potential implicatures the user may draw from NL responses, in particular when 
the response is not direct. 

List of topics:

- Methodologies for intelligently answering questions, 

- New types of questions and related KR, pragmatic and linguistic paradigms: 
  procedural questions (how), causal questions (why), questions with comparative expressions, 
  questions with negation, etc. 

- Reasoning aspects:
    * information fusion,
    * search criteria expansion models (e.g. relaxation techniques),
    * summarization and intensional answers,
    * reasoning under uncertainty or with incomplete knowledge,
    * Detecting and resolving query failure (due to e.g. incomplete data, misconceptions or 
      false presuppositions) 

- Knowledge representation and integration:
    * levels of knowledge involved (e.g. ontologies, domain knowledge),
    * knowledge extraction models and techniques to optimize response accuracy,
    * coherence and integration. 

- Flexible and interactive systems possibly including a user model,

- Pragmatic dimensions of intelligently answering questions:
    * user intentions, plans and goals recognition in questions,
    * conversational implicatures in responses,
    * principles for the design of cooperative systems. 

- Language processing:
    * question processing : parameters of interest for response production,
    * response generation (e.g. lexical choice, templates),
    * use of language resources for reasoning in question-answering,
    * explanation production (showing sources and inferences, reporting data incompleteness, etc.) 

- Evaluation
    * End-to-end evaluation of complex question types,
    * Intrinsic evaluation of inference methods,
    * Data-intensive vs knowledge-intensive methods,
    * portability techniques for closed domains.
The goal of this workshop is to enhance cooperation between participants with an AI background 
and the NLP and question-answering communities. Contributors must be opened to interactions with 
the different workshop areas. The programme committee will care to have a balanced number of 
participants from the different areas concerned: reasoning and inference, knowledge representation, 
NLP (in particular language generation), question-answering, human language technology and 
Although papers will obviously have a dominant theme, it is important that they contain material 
from at least 2 disciplines of the workshop (AI, NLP, pragmatics, ...). 
To encourage an athmosphere appropriate for a workshop, we plan to:
    - have a 15mn discussion at the end of each session,
    - have a panel on future directions of intelligent question-answering and on how the 
different disciplines can interact as optimally as possible,
    - have a session of demonstrations and posters. 

Submission format:
We welcome short papers (max 5 pages), describing projects or ongoing research and long papers 
(max. 10 pages), that relate more established results. Papers must be sent in .pdf format. 
The format to use for papers and abstracts is the same as for IJCAI. Please follow the IJCAI 
formatting instructions and use the supplied Word templates or Latex sources. The title page 
(no separate title page is needed) should include the following information: 
Authors' names, affiliations, and email addresses 
Topic(s) of the above list, as appropriate 
Abstract (short summary up to 5 lines) 


March 10: paper submissions (sent to benamara at irit dot fr) 
April 20: acceptance/rejection notification 
May 15: final papers due, camera-ready 
May 25: manuscript sent to IJCAI for printing by organizers. 


All accepted papers (long and short) will be published in the workshop proceedings. 
A book publication is under project. 

The registration fees include attendance at the workshop and a copy of the workshop 
proceedings. Registration instructions will be posted here. 

Workshop co-chairs and contact persons:
Dr. Farah Benamara and Dr. Patrick Saint-Dizier (benamara at irit dot fr, stdizier at irit dot fr)
Programme committee decisions will be co-chaired with:
Dr. Marie-Francine Moens (marie-france dot moens at law dot kuleuwen dot ac dot be)
Programme Committee:
Farah Benamara, IRIT, France
Johan Bos, University of Edinburgh, UK
Sanda Harabagiu, University of Texas, USA 
Eduard Hovy, ISI, USA 
Daniel Kayser, LIPN, France
Mark Maybury, The MITRE Corp., USA
Michael Minock, University of Umea, Sweden 
Marie-Francine Moens, KUL, Belgium 
Jacques Moeschler, Geneva university, Switzerland
Dan Moldovan, University of Texas, USA
John Prager, IBM, USA
Ehud Reiter, University of Aberdeen, UK
Maarten de Rijke, University of Amsterdam, The Netherlands
Gérard Sabah, LIMSI, CNRS, France
Patrick Saint Dizier, IRIT, CNRS, France 
Manfred Stede, University of Potsdam, Germany
Mathiew Stone, Center of Cognitive Science, Rutgers, USA
Kees Van Deemter, University of Aberdeen, UK
Ellen Voorhees, NIST, USA
Bonnie Webber, University of Edinburgh, UK