Music Recommendation Based on Information of User Profiles, Music Genres and User Ratings

Ja Hwung Su*, Chu Yu Chin, Hsiao Chuan Yang, S. Tseng, Sun Yuan Hsieh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

Music data has been becoming bigger and bigger in recent years. It makes online music stores hard to provide the users with good personalized services. Therefore, a number of past studies were proposed for effectively retrieving the user preferences on music. However, they countered problems such as new user, new item and rating sparsity. To cope with these problems, in this paper, we propose a creative method that integrates information of user profiles, music genres and user ratings. In terms of solving problem of new user, the user similarities can be calculated by the profiles instead of ratings. By the user similarities, the unknown ratings can be predicted using user-based Collaborative Filtering. In terms of solving problem of rating sparsity, the unknown ratings are initialized by ratings of music genres. Even facing new music items, the rating data will not be sparse due to imputing the initialized ratings. Because the rating data is enriched, the user preference can be retrieved by item-based Collaborative Filtering. The experimental results reveal that, our proposed method performs more promising than the compared methods in terms of Root Mean Squared Error.

Original languageEnglish
Title of host publicationIntelligent Information and Database Systems - 10th Asian Conference, ACIIDS 2018, Proceedings
EditorsHoang Pham, Ngoc Thanh Nguyen, Bogdan Trawinski, Duong Hung Hoang, Tzung-Pei Hong
PublisherSpringer Verlag
Pages528-538
Number of pages11
ISBN (Print)9783319754161
DOIs
StatePublished - 1 Jan 2018
Event10th International scientific conferences on research and applications in the field of intelligent information and database systems, ACIIDS 2018 - Dong Hoi City, Viet Nam
Duration: 19 Mar 201821 Mar 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10751 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International scientific conferences on research and applications in the field of intelligent information and database systems, ACIIDS 2018
CountryViet Nam
CityDong Hoi City
Period19/03/1821/03/18

Keywords

  • Collaborative filtering
  • Music recommendation
  • New user
  • Rating sparsity
  • User-based

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