ENSM-SE at INEX 2009 : Scoring with Proximity and Semantic Tag Information

Michel Beigbeder 1 Amélie Imafouo 1 Annabelle Mercier 2
1 RIM-ENSMSE - Département Réseaux, Information, Multimédia
2 LCIS - Laboratoire de Conception et d'Intégration des Systèmes
Abstract : We present in this paper some experiments on the Wikipedia collection used in the INEX 2009 evaluation campaign with an information retrieval method based on proximity. The idea of the method is to assign to each position in the document a fuzzy proximity value depending on its closeness to the surrounding keywords. These proximity values can then be summed on any range of text - including any passage or any element - and after normalization this sum is used as the relevance score for the extent. To take into account the semantic tags, we define a contextual operator which allow to consider at query time only the occurrences of terms that appear in a given semantic context.
Type de document :
Chapitre d'ouvrage
Focused Retrieval and Evaluation, Springer Berlin / Heidelberg, pp.Pages 49 - 58, 2010, 〈10.1007/978-3-642-14556-8_6〉
Liste complète des métadonnées
https://hal-emse.ccsd.cnrs.fr/emse-00674290
Contributeur : Florent Breuil <>
Soumis le : lundi 27 février 2012 - 09:38:56
Dernière modification le : lundi 9 avril 2018 - 12:22:18

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ISCODE-ENSMSE | UR-LSTI-ENSMSE | ISCOD-ENSMSE | RIM-ENSMSE | EMSE | FAYOL-ENSMSE | UGA | LCIS

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Michel Beigbeder, Amélie Imafouo, Annabelle Mercier. ENSM-SE at INEX 2009 : Scoring with Proximity and Semantic Tag Information. Focused Retrieval and Evaluation, Springer Berlin / Heidelberg, pp.Pages 49 - 58, 2010, 〈10.1007/978-3-642-14556-8_6〉. 〈emse-00674290〉

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