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A Priori Relevance Based On Quality and Diversity Of Social Signals

Badache, Ismail and Boughanem, Mohand A Priori Relevance Based On Quality and Diversity Of Social Signals. (2015) In: ACM SIGIR Special Interest Group on Information Retrieval (SIGIR 2015), 9 August 2015 - 13 August 2015 (Santiago, Chile).

(Document in English)

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Official URL: http://dx.doi.org/10.1145/2766462.2767807


Social signals (users' actions) associated with web resources (documents) can be considered as an additional information that can play a role to estimate a priori importance of the resource. In this paper, we are particularly interested in: first, showing the impact of signals diversity associated to a resource on information retrieval performance; second, studying the influence of their social networks origin on their quality. We propose to model these social features as prior that we integrate into language model. We evaluated the effectiveness of our approach on IMDb dataset containing 167438 resources and their social signals collected from several social networks. Our experimental results are statistically significant and show the interest of integrating signals diversity in the retrieval process.

Item Type:Conference or Workshop Item (Paper)
Additional Information:Thanks to ACM New York, NY, USA ©2015. The definitive version is available at http://www.acm.org/publications The original PDF of the article can be found at : http://dl.acm.org/citation.cfm?id=2767807
HAL Id:hal-01283948
Audience (conference):International conference proceedings
Uncontrolled Keywords:
Institution:Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Laboratory name:
Deposited On:07 Mar 2016 09:32

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