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Personality-Aware Collaborative Filtering: An Empirical Study in Multiple Domains with Facebook Data

  • Ignacio Fernández-Tobías
  • Iván Cantador
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 188)

Abstract

In this paper we investigate the incorporation of information about the users’ personality into a number of collaborative filtering methods, aiming to address situations of user preference scarcity. Through empirical experiments on a multi-domain dataset obtained from Facebook, we show that the proposed personality-aware collaborative filtering methods effectively –and consistently in the studied domains– increase recommendation performance, in terms of both precision and recall. We also present an analysis of relationships existing between user preferences and personality for the different domains, considering the users’ gender and age.

Keywords

recommender systems collaborative filtering personality user similarity 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Ignacio Fernández-Tobías
    • 1
  • Iván Cantador
    • 1
  1. 1.Universidad Autónoma de MadridMadridSpain

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