FNM-based and RFCM-based fuzzy clustering for tri-relational data

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

Abstract

In this paper, some fuzzy clustering methods are proposed for relational data which represents the dissimilarity for triples of data points. One method is based on the fuzzy nonmetric model and the other is on the relational fuzzy c-means. Each method has two options of fuzzification; the standard and the entropy-regularization. Through some numerical experiments, the feature of the proposed methods is discussed.

Original languageEnglish
Title of host publication6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012
Pages1982-1987
Number of pages6
DOIs
Publication statusPublished - 2012 Dec 1
Event2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012 - Kobe, Japan
Duration: 2012 Nov 202012 Nov 24

Publication series

Name6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012

Conference

Conference2012 Joint 6th International Conference on Soft Computing and Intelligent Systems, SCIS 2012 and 13th International Symposium on Advanced Intelligence Systems, ISIS 2012
CountryJapan
CityKobe
Period12/11/2012/11/24

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software

Fingerprint Dive into the research topics of 'FNM-based and RFCM-based fuzzy clustering for tri-relational data'. Together they form a unique fingerprint.

  • Cite this

    Kanzawa, Y. (2012). FNM-based and RFCM-based fuzzy clustering for tri-relational data. In 6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012 (pp. 1982-1987). [6505050] (6th International Conference on Soft Computing and Intelligent Systems, and 13th International Symposium on Advanced Intelligence Systems, SCIS/ISIS 2012). https://doi.org/10.1109/SCIS-ISIS.2012.6505050