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Document Priors Based On Time-Sensitive Social Signals

  • Ismail Badache
  • Mohand Boughanem
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9022)

Abstract

Relevance estimation of a Web resource (document) can benefit from using social signals. In this paper, we propose a language model document prior exploiting temporal characteristics of social signals. We assume that a priori significance of a document depends on the date of users actions (social signals) and on the publication date (first occurrence) of the document. Particularly, rather than estimating the priors by simply counting signals related to the document, we bias this counting by taking into account the dates of the resource and the action. We evaluate our approach on IMDb dataset containing 167438 resources and their social data collected from several social networks. The experiments show the interest of temporally-aware signals at capturing relevant resources.

Keywords

Social Information Retrieval Social Signals Signal Time Resource Publication Date Social Ranking Language Models 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Ismail Badache
    • 1
  • Mohand Boughanem
    • 1
  1. 1.IRIT - Paul Sabatier UniversityToulouseFrance

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