Five-Factor Musical Preference Prediction for Solving New User Cold-Start Problem in Content-Based Music Recommender System

Keisuke Okada, Phan Xuan Tan, Eiji Kamioka

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Recent years witness a boom in music recommender systems due to the success of online streaming services. Even though such systems have brought relatively high-quality recommendations to the users, they are still facing the cold-start problem, especially for new user case. This problem happens when the system does not have information about the new user's preferences to provide recommendations. Therefore, effectively predicting musical preferences for the new user becomes vital. In this paper, we leverage a five-factor MUSIC model which is characterized by Mellow, Unpretentious, Sophisticated, Intense, and Contemporary to represent the user's preference. Then, towards solving the new user cold-start problems in the content-based music recommender system, we propose a method to predict the five-factor preference profile of the novel user. We consider an early-stage scenario when there are no and few rating data of the user available in the system. Accordingly, we first use the information of age and brain type extracted from questionnaires to build regression models. These models are used to predict the first five-factor musical preference profile for initial recommendations. We then estimate the second five-factor profile based on the user's rating data and linearly combine it with the first profile for improving recommendations. The results demonstrated the effectiveness of the proposed method in predicting the musical preference of the new user in the assumed scenario.

Original languageEnglish
Title of host publicationIISA 2021 - 12th International Conference on Information, Intelligence, Systems and Applications
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665400329
DOIs
Publication statusPublished - 2021 Jul 12
Event12th International Conference on Information, Intelligence, Systems and Applications, IISA 2021 - Virtual, Chania Crete, Greece
Duration: 2021 Jul 122021 Jul 14

Publication series

NameIISA 2021 - 12th International Conference on Information, Intelligence, Systems and Applications

Conference

Conference12th International Conference on Information, Intelligence, Systems and Applications, IISA 2021
Country/TerritoryGreece
CityVirtual, Chania Crete
Period21/7/1221/7/14

Keywords

  • cold-start problem
  • five-factor MUSIC model
  • music recommender system

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management

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