New technique to deal with verbose queries in social book search

Abstract : Verbose query reduction and query term weighting are automatic techniques to deal with verbose queries. The objective is either to assign an appropriate weight to query terms according to their importance in the topic, or outright remove unsuitable terms from the query and keep only the suitable terms to the topic and user's need. These techniques improve performance and provide good results for ad hoc information retrieval. In this paper we propose a new approach to deal with long verbose queries in Social Information Retrieval (SIR) by taking Social Book Search as an example. In this approach, a new statistical measure was introduced to reduce and weight terms of verbose queries. Next, we expand the query by exploiting the similar books mentioned by users in their queries. We find that the proposed approach improves significantly the results.
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Communication dans un congrès
2017 ACM/IEEE/WIC International Conference on Web Intelligence, Aug 2017, Leipzig, Germany. ACM Press, 8, pp.799-806, 2017, 〈10.1145/3106426.3106481〉
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Contributeur : Patrice Bellot <>
Soumis le : vendredi 25 janvier 2019 - 10:35:54
Dernière modification le : jeudi 7 février 2019 - 15:29:32

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Distributed under a Creative Commons Paternité - Pas d'utilisation commerciale 4.0 International License

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Messaoud Chaa, Omar Nouali, Patrice Bellot. New technique to deal with verbose queries in social book search. 2017 ACM/IEEE/WIC International Conference on Web Intelligence, Aug 2017, Leipzig, Germany. ACM Press, 8, pp.799-806, 2017, 〈10.1145/3106426.3106481〉. 〈hal-01794695〉

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