Bruce Ferwerda, Markus Schedl,
"Personality-Based User Modeling for Music Recommender Systems"
: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery In Databases (ECML PKDD), 9-2016
Original Titel:
Personality-Based User Modeling for Music Recommender Systems
Sprache des Titels:
Englisch
Original Buchtitel:
Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery In Databases (ECML PKDD)
Original Kurzfassung:
Applications are getting increasingly interconnected. Although
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.
Forschungs-