It is well known that human reasoning and decision-making are strongly influenced by psychological aspects. Recent works explore the adoption of personality traits to provide personalized recommendations. In this article, we report experimental results obtained with implicit recognition of Big Five personality traits from users’ text reviews. Hence, we present a personality-based recommender system with the analysis of the overall users’ satisfaction regarding the list of recommended items, showing promising results.

Recommendations with Personality Traits Extracted from Text Reviews

DI RIENZO, ANTONELLA;
2016

Abstract

It is well known that human reasoning and decision-making are strongly influenced by psychological aspects. Recent works explore the adoption of personality traits to provide personalized recommendations. In this article, we report experimental results obtained with implicit recognition of Big Five personality traits from users’ text reviews. Hence, we present a personality-based recommender system with the analysis of the overall users’ satisfaction regarding the list of recommended items, showing promising results.
Intelligent Distributed Computing IX
978-3-319-25017-5
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/985737
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