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Article Dans Une Revue Information Processing and Management Année : 2014

On domain expertise-based roles in collaborative information retrieval

Laure Soulier
Wahiba Bahsoun
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Résumé

Collaborative information retrieval involves retrieval settings in which a group of users collaborates to satisfy the same underlying need. One core issue of collaborative IR models involves either supporting collaboration with adapted tools or developing IR models for a multiple-user context and providing a ranked list of documents adapted for each collaborator. In this paper, we introduce the first document-ranking model supporting collaboration between two users characterized by roles relying on different domain expertise levels. Specifically, we propose a two-step ranking model: we first compute a document-relevance score, taking into consideration domain expertise-based roles. We introduce specificity and novelty factors into language-model smoothing, and then we assign, via an Expectation–Maximization algorithm, documents to the best-suited collaborator. Our experiments employ a simulation-based framework of collaborative information retrieval and show the significant effectiveness of our model at different search levels.
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Dates et versions

hal-01118658 , version 2 (28-01-2015)
hal-01118658 , version 1 (19-02-2015)

Identifiants

Citer

Laure Soulier, Lynda Tamine, Wahiba Bahsoun. On domain expertise-based roles in collaborative information retrieval. Information Processing and Management, 2014, vol. 50 (n° 5), pp. 752-774. ⟨10.1016/j.ipm.2014.04.002⟩. ⟨hal-01118658v1⟩
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