Performance comparison of collaborative filtering using fuzzy clustering for spherical data

Tadafumi Kondo, Yuchi Kanzawa

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

1 Citation (Scopus)

Abstract

GroupLens is the representative neighborhood-based algorithm for collaborative filtering task, where the definition of 'neighborhood' is heuristic. This study proposes determining the neighborhood using fuzzy clustering for spherical data, and compares three fuzzy clustering for spherical data been proposed with GroupLens algorithm, using two real datasets. The experimental result shows that the proposal achieved higher recommendation accuracy for all two datasetsand that all three clustering algorithms help determining more adequate neighbor-hood than the conventionally determined neighborhood.

Original languageEnglish
Title of host publicationProceedings - 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages644-647
Number of pages4
ISBN (Electronic)9781538626337
DOIs
Publication statusPublished - 2019 May 15
EventJoint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2018 - Toyama, Japan
Duration: 2018 Dec 52018 Dec 8

Publication series

NameProceedings - 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2018

Conference

ConferenceJoint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2018
CountryJapan
CityToyama
Period18/12/518/12/8

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Keywords

  • Collaborative Filtering
  • Fuzzy Clustering
  • Spherical Data

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Logic
  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Science Applications
  • Theoretical Computer Science

Cite this

Kondo, T., & Kanzawa, Y. (2019). Performance comparison of collaborative filtering using fuzzy clustering for spherical data. In Proceedings - 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2018 (pp. 644-647). [8716226] (Proceedings - 2018 Joint 10th International Conference on Soft Computing and Intelligent Systems and 19th International Symposium on Advanced Intelligent Systems, SCIS-ISIS 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SCIS-ISIS.2018.00108