Personality-Based User Modeling for Music Recommender Systems

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9853)

Abstract

Applications are getting increasingly interconnected. Al-though the interconnectedness provide new ways to gather information about the user, not all user information is ready to be directly implemented in order to provide a personalized experience to the user. Therefore, a general model is needed to which users’ behavior, preferences, and needs can be connected to. In this paper we present our works on a personality-based music recommender system in which we use users’ personality traits as a general model. We identified relationships between users’ personality and their behavior, preferences, and needs, and also investigated different ways to infer users’ personality traits from user-generated data of social networking sites (i.e., Facebook, Twitter, and Instagram). Our work contributes to new ways to mine and infer personality-based user models, and show how these models can be implemented in a music recommender system to positively contribute to the user experience.

Keywords

Personalization Music recommender systems 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  1. 1.Department of Computational PerceptionJohannes Kepler UniversityLinzAustria

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