CBCG: A Clustering Algorithm Based on Bidirectional Conical Information Granularity

In this article, we propose a novel center-based clustering algorithm based on bidirectional conical information granularity. The main purpose is to fully absorb the semantic information of the ordinal relationship between objects to improve the performance of central clustering in identifying inter...

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Bibliographic Details

Published in:	IEEE transactions on fuzzy systems Vol. 32; no. 8; pp. 4388 - 4400
Main Authors:	Yu, Bin, Zheng, Zijian, Cai, Mingjie, Pedrycz, Witold, Xu, Zeshui
Format:	Journal Article
Language:	English
Published:	IEEE 01.08.2024
Subjects:	<named-content xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" content-type="math" xlink:type="simple"> <inline-formula> <tex-math notation="LaTeX"> k</tex-math> </inline-formula> </named-content>-bidirectional conical information granularity Bidirectional conical information granularity center-based clustering Clustering algorithms Clustering methods Data mining Data models fuzzy importance degree (FID) Fuzzy systems Granular computing Semantics two-step division
ISSN:	1063-6706, 1941-0034
Online Access:	Get full text
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