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A Collaborative Document Ranking Model for a Multi-faceted Search

Laure Soulier 1 Lynda Tamine 1 Wahiba Bahsoun 1
1 IRIT-SIG - Systèmes d’Informations Généralisées
IRIT - Institut de recherche en informatique de Toulouse
Abstract : This paper presents a novel collaborative document ranking model which aims at solving a complex information retrieval task in-volving a multi-faceted information need. For this purpose, we consider a group of users, viewed as experts, who collaborate by addressing the different query facets. We propose a two-step algorithm based on a rele-vance feedback process which first performs a document scoring towards each expert and then allocates documents to the most suitable experts using the Expectation-Maximisation learning-method. The performance improvement is demonstrated through experiments using TREC inter-active benchmark.
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Submitted on : Wednesday, January 28, 2015 - 5:35:45 PM
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Laure Soulier, Lynda Tamine, Wahiba Bahsoun. A Collaborative Document Ranking Model for a Multi-faceted Search. 9th Asia Information Retrieval Societies Conference, AIRS 2013, Dec 2013, Singapour, Singapore. pp.109 - 120, ⟨10.1007/978-3-642-45068-6_10⟩. ⟨hal-01110710⟩



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