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Harnessing Social Signals to Enhance a Search

Badache, Ismail and Boughanem, Mohand Harnessing Social Signals to Enhance a Search. (2014) Web Intelligence (WI) and Intelligent Agent Technologies (IAT), 2014 IEEE/WIC/ACM International Joint Conferences on, 1. 303-309.

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Official URL: http://dx.doi.org/10.1109/WI-IAT.2014.48


This paper describes an approach of information retrieval which takes into account social signals associated with Web resources to estimate its relevance to a query. We show how these data, which are in the form of actions within social activities (e.g. like, tweet), can be exploited to quantify social properties such as popularity and reputation. We propose a model that combines the social relevance, estimated from these properties, with the conventional textual relevance. We evaluated the effectiveness of our approach on IMDb dataset containing 32706 resources and their social characteristics collected from several social networks. We used also the selected criteria to learn models to determine their effectiveness in information retrieval. Our experimental results are promising and show the interest of integrating social signals in retrieval model to enhance a search.

Item Type:Article
Additional Information:Thanks to IEEE editor. The definitive version is available at http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6927557
HAL Id:hal-01109811
Audience (journal):International peer-reviewed journal
Audience (conference):National 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:27 Jan 2015 09:18

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