Open AccessAnswering French Questions in English by Exploiting Results from Several Sources of Information
Author(s) -
Brigitte Grau,
Gabriel Illouz,
Laura Monceaux,
Isabelle Robba,
Anne Vilnat,
Guillaume Bourdil,
Faïza Elkateb-Gara,
Olivier Ferret,
B. Mathieu
Publication year - 2005
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
ISBN - 3-540-27420-0
DOI - 10.1007/11519645_46
Subject(s) - clef , computer science , information retrieval , question answering , natural language processing , world wide web , artificial intelligence , engineering , task (project management) , systems engineering
Our bilingual QA system MUSCLEF, is based on QALC, the monolingual system with which we have participated in the previous TREC, where our best results were obtained when we combined the results of several searches. First, QALC searched a reliable document collection for answers, and second the WEB. We kept this strategy for CLEF, returning two runs. In the first one, we modified QALC so as to handle multilinguality by translating the terms identified in the question. In the second run, we combined the results of the first run with those obtained by first translating the question, then applying the full QALC strategy i.e. searching both the collection and the WEB. The final evaluation confirms the fact that the best results are obtained by combining different sources of information.
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