A Collaborative Document Ranking Model for a Multi-faceted Search

Laure Soulier (1) , Lynda Tamine (1) , Wahiba Bahsoun (1, 2)

1 IRIT-SIG - Systèmes d’Informations Généralisées
2 UT3 - Université Toulouse III - Paul Sabatier

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.

Mots clés: Multi-faceted search; Collaborative information retrieval

Domaines: Recherche d'information [cs.IR]

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⟩