New Technique to Deal With Verbose Queries in Social Book Search

dc.contributor.authorChaa, Messaoud
dc.contributor.authorNouali, Omar
dc.contributor.authorBellot, Patrice
dc.date.accessioned2017-06-15T08:47:43Z
dc.date.available2017-06-15T08:47:43Z
dc.date.issued2017
dc.description.abstractVerbose 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 Re-trieval (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 he query by exploiting the similar books mentioned by users in their queries. We find that the proposed approach improves significantly the results.fr_FR
dc.identifier.isrnCERIST-DRDSI--17-000000013--DZfr_FR
dc.identifier.urihttp://dl.cerist.dz/handle/CERIST/894
dc.publisherCERIST
dc.relation.ispartofRapports de recherche internes
dc.relation.placeAlger
dc.structureRecherche, Filtrage et Traitement Automatique de l'Informationfr_FR
dc.subjectVerbose Query Reductionfr_FR
dc.subjectQuery Term Weightingfr_FR
dc.subjectQuey Expansionfr_FR
dc.subjectTf.Iqffr_FR
dc.subjectSocial Book Searchfr_FR
dc.subjectStop-Word Listfr_FR
dc.titleNew Technique to Deal With Verbose Queries in Social Book Searchfr_FR
dc.typeTechnical Report
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