Information Retrieval System Using Latent Contextual Relevance

Minoru Sasaki, Hiroyuki Shinnou


Abstract
When the relevance feedback, which is one of the most popular information retrieval model, is used in an information retrieval system, a related word is extracted based on the first retrival result. Then these words are added into the original query, and retrieval is performed again using updated query. Generally, Using such query expansion technique, retrieval performance using the query expansion falls in comparison with the performance using the original query. As the cause, there is a few synonyms in the thesaurus and although some synonyms are added to the query, the same documents are retireved as a result. In this paper, to solve the problem over such related words, we propose latent context relevance in consideration of the relevance between query and each index words in the document set.
Anthology ID:
L04-1241
Volume:
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)
Month:
May
Year:
2004
Address:
Lisbon, Portugal
Editors:
Maria Teresa Lino, Maria Francisca Xavier, Fátima Ferreira, Rute Costa, Raquel Silva
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2004/pdf/413.pdf
DOI:
Bibkey:
Cite (ACL):
Minoru Sasaki and Hiroyuki Shinnou. 2004. Information Retrieval System Using Latent Contextual Relevance. In Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04), Lisbon, Portugal. European Language Resources Association (ELRA).
Cite (Informal):
Information Retrieval System Using Latent Contextual Relevance (Sasaki & Shinnou, LREC 2004)
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PDF:
http://www.lrec-conf.org/proceedings/lrec2004/pdf/413.pdf