RELEVANCE FEEDBACK AS AN INDICATOR TO SELECT THE BEST SEARCH ENGINE - Evaluation on TREC Data

Gilles Hubert; Josiane Mothe

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Paper

RELEVANCE FEEDBACK AS AN INDICATOR TO SELECT THE BEST SEARCH ENGINE - Evaluation on TREC Data

Topics: Modeling of Distributed Systems

In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS, 184-189, 2007 , Funchal, Madeira, Portugal

Authors: Gilles Hubert and Josiane Mothe

Affiliation: Institut de Recherche en Informatique de Toulouse; ERT34, IUFM, France

Keyword(s): Information Retrieval, relevance feedback, system selection, system fusion.

Related Ontology Subjects/Areas/Topics: Enterprise Information Systems ; Information Systems Analysis and Specification ; Modeling of Distributed Systems

Abstract: This paper explores information retrieval system variability and takes advantage of the fact two systems can retrieve different documents for a given query. More precisely, our approach is based on data fusion (fusion of system results) by taking into account local performances of each system. Our method considers the relevance of the very first documents retrieved by different systems and from this information selects the system that will perform the retrieval for the user. We found that this principle improves the performances of about 9%. Evaluation is based on different years of TREC evaluation program (TREC 3, 5, 6 and 7), TREC-adhoc tracks. It considers the two and five best systems that participate to TREC the corresponding year.

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Paper citation in several formats:

Hubert, G. and Mothe, J. (2007). RELEVANCE FEEDBACK AS AN INDICATOR TO SELECT THE BEST SEARCH ENGINE - Evaluation on TREC Data. In Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-972-8865-90-0; ISSN 2184-4992, SciTePress, pages 184-189. DOI: 10.5220/0002361301840189

@conference{iceis07,
author={Gilles Hubert. and Josiane Mothe.},
title={RELEVANCE FEEDBACK AS AN INDICATOR TO SELECT THE BEST SEARCH ENGINE - Evaluation on TREC Data},
booktitle={Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2007},
pages={184-189},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002361301840189},
isbn={978-972-8865-90-0},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the Ninth International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - RELEVANCE FEEDBACK AS AN INDICATOR TO SELECT THE BEST SEARCH ENGINE - Evaluation on TREC Data
SN - 978-972-8865-90-0
IS - 2184-4992
AU - Hubert, G.
AU - Mothe, J.
PY - 2007
SP - 184
EP - 189
DO - 10.5220/0002361301840189
PB - SciTePress