HPCF: Hybrid Music Group Recommendation System based on Item Popularity and Collaborative Filtering

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

1 Citation (Scopus)

Abstract

Group recommendation system is designed to pleasure a certain group of people by providing recommendation lists to prevent information overload. This paper proposes HPCF, which combines item popularity and preference of the group members to optimize the quality of recommendation. Evaluation results show that the HPCF outperforms popularity-based methods and Singular Value Decomposition based methods. In our experiments, HPCF scheme improves the accuracy of recommendation by 8.7% to 19.8% in different conditions.

Original languageEnglish
Title of host publicationProceedings - 2020 International Computer Symposium, ICS 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages43-49
Number of pages7
ISBN (Electronic)9781728192550
DOIs
Publication statusPublished - 2020 Dec
Event2020 International Computer Symposium, ICS 2020 - Tainan, Taiwan
Duration: 2020 Dec 172020 Dec 19

Publication series

NameProceedings - 2020 International Computer Symposium, ICS 2020

Conference

Conference2020 International Computer Symposium, ICS 2020
Country/TerritoryTaiwan
CityTainan
Period20-12-1720-12-19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Information Systems
  • Information Systems and Management
  • Computational Mathematics

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