On Collaborative Filtering with Possibilistic Clustering for Spherical Data Based on Tsallis Entropy

Yuchi Kanzawa

doi:10.1007/978-3-030-26773-5_17

On Collaborative Filtering with Possibilistic Clustering for Spherical Data Based on Tsallis Entropy

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper proposes a collaborative filtering (CF) method using possibilistic clustering for spherical data based on Tsallis entropy. This study was motivated by a previous work, which showed that adopting fuzzy clustering for spherical data in CF tasks provided better recommendation accuracy than fuzzy clustering for categorical-multivariate data. Moreover, possibilistic clustering algorithms are naturally more robust to noise than fuzzy clustering. The results of experiments conducted on an artificial dataset and one real dataset indicate that the proposed method is better than the conventional methods in terms of recommendation accuracy.

Original language	English
Title of host publication	Modeling Decisions for Artificial Intelligence - 16th International Conference, MDAI 2019, Proceedings
Editors	Vicenç Torra, Yasuo Narukawa, Gabriella Pasi, Marco Viviani
Publisher	Springer Verlag
Pages	189-200
Number of pages	12
ISBN (Print)	9783030267728
DOIs	https://doi.org/10.1007/978-3-030-26773-5_17
Publication status	Published - 2019 Jan 1
Event	16th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2019 - Milan, Italy Duration: 2019 Sept 4 → 2019 Sept 6

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11676 LNAI
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2019
Country/Territory	Italy
City	Milan
Period	19/9/4 → 19/9/6

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science(all)

Access to Document

10.1007/978-3-030-26773-5_17

Cite this

Kanzawa, Y. (2019). On Collaborative Filtering with Possibilistic Clustering for Spherical Data Based on Tsallis Entropy. In V. Torra, Y. Narukawa, G. Pasi, & M. Viviani (Eds.), Modeling Decisions for Artificial Intelligence - 16th International Conference, MDAI 2019, Proceedings (pp. 189-200). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11676 LNAI). Springer Verlag. https://doi.org/10.1007/978-3-030-26773-5_17

On Collaborative Filtering with Possibilistic Clustering for Spherical Data Based on Tsallis Entropy. / Kanzawa, Yuchi.
Modeling Decisions for Artificial Intelligence - 16th International Conference, MDAI 2019, Proceedings. ed. / Vicenç Torra; Yasuo Narukawa; Gabriella Pasi; Marco Viviani. Springer Verlag, 2019. p. 189-200 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11676 LNAI).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kanzawa, Y 2019, On Collaborative Filtering with Possibilistic Clustering for Spherical Data Based on Tsallis Entropy. in V Torra, Y Narukawa, G Pasi & M Viviani (eds), Modeling Decisions for Artificial Intelligence - 16th International Conference, MDAI 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11676 LNAI, Springer Verlag, pp. 189-200, 16th International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2019, Milan, Italy, 19/9/4. https://doi.org/10.1007/978-3-030-26773-5_17

Kanzawa Y. On Collaborative Filtering with Possibilistic Clustering for Spherical Data Based on Tsallis Entropy. In Torra V, Narukawa Y, Pasi G, Viviani M, editors, Modeling Decisions for Artificial Intelligence - 16th International Conference, MDAI 2019, Proceedings. Springer Verlag. 2019. p. 189-200. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-26773-5_17

Kanzawa, Yuchi. / On Collaborative Filtering with Possibilistic Clustering for Spherical Data Based on Tsallis Entropy. Modeling Decisions for Artificial Intelligence - 16th International Conference, MDAI 2019, Proceedings. editor / Vicenç Torra ; Yasuo Narukawa ; Gabriella Pasi ; Marco Viviani. Springer Verlag, 2019. pp. 189-200 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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On Collaborative Filtering with Possibilistic Clustering for Spherical Data Based on Tsallis Entropy

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