KRAQ'05: KNOWLEDGE and REASONING for ANSWERING QUESTIONS
July 30th, 2005,
location: University Buildings, please consult the main IJCAI web page
Sponsored by France-Telecom
Link to download the proceedings : KRAQ05
Session 1 8.30-10.30
Being Erlan Shen: Identifying Answerable Questions,
H. Yu, C. Sable, USA.
Reasoning over Depedency Relations for QA,
G. Bouma, J. Mur, G. Van Noord, the Netherlands.
Towards Answering procedural Questions,
F. Aouladomar, France.
Towards a Framework for the Summarization of Help-Desk Responses
Y. Marom, I. Zukerman, Australia.
10h30-11h00 Coffee break
11h00 – 11h45 Invited talk by Johan Bos, UK
11h45-12h15 Short papers and posters
Toward Question Answering for Simulation,
M. Core et ali. USA
A Question-Answering System for Portuguese,
C. Prolo et ali., Brasil and Portugal
Semantic Knowledge in Question-Answering Systems,
V. Barbier et ali., France
A Typology and Feature Set for Questions,
L. Aunimo, Finland
Recognition of Alternation Paraphrases: a robust and exhaustive symbolic
M. Amoia and C. Gardent, France.
12h15-13h30 lunch break and poster visits
Session 2 13h30-15h00
On the Effective Use of Cyc in a Question-answering System,
J. Curtis et ali., USA.
An Inference Model for Semantic Entailment and Question Answering
R. de Salvo Braz et ali., USA.
Using Information Fusion for Open-Domain Question Answering,
T. Dalmas, B. Webber, UK.
15h00-15h30 Coffee Break
Session 3 15h30-16h45
Supervised Machine learning Techniques for Question Answering,
I. Zukerman et ali., Australia.
Invited talk : Marie-Francine Moens, Belgium (45 mns)
Panel Session: 17h00 – 18h00
Moderators: M. Minock (Sweden) and T. Poibeau (France)
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
(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.)
* 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 pragmatics.
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,
- plan demos on portable machines.
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
and use the supplied
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)
- April 1st: paper submissions (sent to both: firstname.lastname@example.org and email@example.com)
- April 30: acceptance/rejection notification
- May 18: 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.
Dr. Farah Benamara and Dr. Patrick Saint-Dizier (firstname.lastname@example.org, email@example.com)
Programme committee decisions will be co-chaired with:
Dr. Marie-Francine Moens (firstname.lastname@example.org)
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