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A Collaborative Document Ranking Model for a Multi-Faceted Search

Soulier, Laure and Tamine, Lynda and Bahsoun, Wahiba A Collaborative Document Ranking Model for a Multi-Faceted Search. (2013) In: Asia Information Retrieval Society Conference - AIRS 2013, 9 December 2013 - 11 December 2013 (Singapore, Singapore).

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Official URL: http://dx.doi.org/10.1007/978-3-642-45068-6_10

Abstract

This paper presents a novel collaborative document ranking model which aims at solving a complex information retrieval task involving 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 relevance 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 interactive benchmark.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to Springer editor. The definitive version is available at http://link.springer.com/chapter/10.1007/978-3-642-45068-6_10
HAL Id:hal-01142942
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - INPT (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UPS (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
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Deposited By: IRIT IRIT
Deposited On:16 Apr 2015 12:12

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