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Fresh and Diverse Social Signals: Any Impacts on Search?

Ismail Badache 1 Mohand Boughanem 2
1 R2I - Recherche d’information et Interactions
LIS - Laboratoire d'Informatique et Systèmes
2 IRIT-IRIS - Recherche d’Information et Synthèse d’Information
IRIT - Institut de recherche en informatique de Toulouse
Abstract : In this paper, we extensively study the impact of social signals (users’ actions) obtained from several social networks on search ranking task. Social signals associated with web resources (documents) can be considered as an additional information that can play a vital role to estimate a priori importance of these resources.Particularly, we are interested in the freshness of signals and their diversity. We hypothesize that the moment (the date) when the user actions occur and the diversity of actions may impact the search performance. We propose to model these heterogeneous social features as document prior. We evaluate the effectiveness of our approach by carrying out extensive experiments on two different INEX datasets, namely SBS and IMDb, enriched with several social signals collected from social networks. Our experimental results consistently demonstrate the interest of integrating fresh and diverse signals in the retrieval process.
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Submitted on : Thursday, March 8, 2018 - 11:49:42 AM
Last modification on : Wednesday, December 2, 2020 - 3:12:15 AM
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Ismail Badache, Mohand Boughanem. Fresh and Diverse Social Signals: Any Impacts on Search?. CHIIR '17 Proceedings of the 2017 Conference on Conference Human Information Interaction and Retrieval, Mar 2017, Oslo, Norway. pp.155-164, ⟨10.1145/3020165.3020177⟩. ⟨hal-01726407⟩



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