Graph Enhanced Fuzzy Clustering for Categorical Data Using a Bayesian Dissimilarity Measure-Reference-Cited by-同舟云学术

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Graph Enhanced Fuzzy Clustering for Categorical Data Using a Bayesian Dissimilarity Measure

Published:2023-03 Issue:3 Volume:31 Page:810-824
ISSN:1063-6706
Container-title:IEEE Transactions on Fuzzy Systems
language:
Short-container-title:IEEE Trans. Fuzzy Syst.

Author:

Zhang Chuanbin¹^ORCID,Chen Long¹^ORCID,Zhao Yin-Ping²^ORCID,Wang Yingxu¹^ORCID,Chen C. L. Philip³^ORCID

Affiliation:

1. Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau, China

2. School of Software, Northwestern Polytechnical University, Xi’an, China

3. School of Computer Science and Engineering, South China University of Technology, Guangzhou, China

Funder

Basic and Applied Basic Research Foundation of Guangdong Province

Science and Technology Development Fund

Macao S.A.R

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Applied Mathematics,Artificial Intelligence,Computational Theory and Mathematics,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/91/10056985/09826411.pdf?arnumber=9826411

Reference53 articles.

1. A survey of distance/similarity measures for categorical data

2. A fuzzy k-modes algorithm for clustering categorical data

3. Unsupervised Coupled Metric Similarity for Non-IID Categorical Data

4. Similarity Measures for Categorical Data: A Comparative Evaluation

5. Manifold-regularized Multitask Fuzzy System Modeling with Low-rank and Sparse Structures in Consequent Parameters

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