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CALL FOR PAPER
Held in conjunction with T A L N 2 0 0 4
Workshop on QUESTION-ANSWERING
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Palais de Congrès
Fès (Maroc)
April 22, 2004
http://www.lpl.univ-aix.fr/jep-taln04/question-answer.htm
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->>>> New deadline : Jannuary 23, 2004
IMPORTANT DATES:
Submission deadline: January 23, 2004
Notification to authors:February 20, 2004
Camera-ready: March 8, 2004
Question-Answering workshop: April 22, 2004
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Facing a question such as «What is the most expensive car in the world?»,
classical search engines return the documents that are the most strongly
linked to the words of the question, sometimes extract the excerpts where
these words are the most numerous, but let the user browse texts to
actually find an answer. This need leads to develop systems that are able
to extract the parts of documents that are the most relevant in relation to
a question, providing either an answer when the question is about a precise
fact or a summary when it is a topical question.
These functions can be implemented only if IR systems are able to analyze
both queries and documents more deeply. As a consequence, question
answering is at the crossing of several research fields: of course, it is
grounded in Information Retrieval but it also concerns Natural Language
Processing (NLP) in an important way and to some extent, fields such as
Machine Learning.
Most QA systems are based on a classical search engine that is enhanced by
a question analysis module, a set of modules for extracting various
linguistic features from documents, such as named entities, terms or
syntactic relations, and a module that relies on all these data for
extracting answers by mixing linguistic and numerical criteria.
Moreover, the QA problem puts forward new functions, or functions that are
still in an embryonic state in current IR systems: evaluating if an answer
to a question exists in a document collection, achieving a synthesis from
multiple or partial answers, using dialog for constructing a query, or text
understanding capabilities for dealing with anaphora, inferences, or for
determining if a set of several answers is coherent.
More precisely, submissions will present a question answering system as a
whole or will focus on one of its processes provided that it is put in the
question answering context. These processes include but are not limited to:
- question analysis: question typology, extraction of the question
focus, of the question context or more generally, of semantic constraints
- named entity recognition: fine-grained named entities, unrestricted
domains
- passage extraction
- full or partial similarity of syntactic structures
- terminological tools: extraction and recognition of terms and their
variants
- extraction and justification of answers: answer patterns,
inferences, paraphrase ...
This workshop is particularly concerned by papers that focus on QA systems
for large collections of documents or the Web but papers about QA systems
for restricted domains or dedicated to knowledge bases or database will
also be taken into account.
Submissions can also tackle cross-domain topics in relation to Question
Answering , such as:
- QA and machine learning: use of machine learning for selecting and
extracting answers to a question but also for building on a large scale
resources that are necessary for QA systems;
- multilingual and crosslingual QA: what are the difficulties for
adapting an existing QA system most of them only work for English to
another language; asking a question in a language and searching an answer
in a collection of documents in another language;
- QA and the Web: using the Web as a source of knowledge or a source
of answers; what are the specific aspects of searching an answer on the Web;
- multi-document QA: fusion and coherence of multiple answers.
SUBMISSION:
Submissions will be minimum 4 page summaries or long papers of no more than
10 pages, written in French or English, according to the style of the main
conference TALN 2004.
The final version will be a long paper.
Submission format will be PDF, but .doc and .ps will be also admitted.
Papers have to be sent to Brigitte.Grau@limsi.fr, with TALN-QA as subject.
ORGANIZATION COMMITTEE
Brigitte Grau, LIMSI, Orsay (responsable)
Olivier Ferret, LIC2M, CEA, Fontenay
Gabriel Illouz, LIMSI, Orsay
Laura Monceaux, IRIN, Nantes
Thierry Poibeau, LIPN, Villetaneuse
Isabelle Robba, LIMSI, Orsay
Anne Vilnat, LIMSI, Orsay
SCIENTIFIC COMMITTEE
Massi-Reza Amini, LIP6, Paris
Patrice Bellot, LIA, Avignon
Mohand Boughanem, IRIT, Toulouse
Jean-Pierre Chevallet, CLIPS, Grenoble
Khalid Choukri, ELDA, Paris
Olivier Collin, France Telecom, Lannion
Olivier Ferret, LIC2M, CEA, Fontenay
Patrick Gallinari, LIP6, Paris
Brigitte Grau, LIMSI, Orsay
Gabriel Illouz, LIMSI, Orsay
Guy Lapalme, RALI, Canada
Claude de Loupy, Sinequa
Jean-Luc Minel, LALICC, Paris
Laura Monceaux, IRIN, Nantes
Thierry Poibeau, LIPN, Villetaneuse
Isabelle Robba, LIMSI, Orsay
Patrick Saint-Dizier, IRIT, Toulouse
Anne Vilnat, LIMSI, Orsay
Pierre Zweigenbaum, STIM, AP-HP Paris
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