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

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 prop...

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Bibliographic Details
Published inE-Commerce and Web Technologies pp. 125 - 137
Main Authors Fernández-Tobías, Ignacio, Cantador, Iván
Format Book Chapter
LanguageEnglish
Published Cham Springer International Publishing 2014
SeriesLecture Notes in Business Information Processing
Subjects
collaborative filtering
personality
recommender systems
user similarity
Online AccessGet full text
ISBN9783319104904
331910490X
ISSN1865-1348
1865-1356
DOI10.1007/978-3-319-10491-1_13

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Summary: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.
ISBN:9783319104904
331910490X
ISSN:1865-1348
1865-1356
DOI:10.1007/978-3-319-10491-1_13