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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Vydáno v:	IEEE transactions on fuzzy systems Ročník 32; číslo 8; s. 4388 - 4400
Hlavní autoři:	Yu, Bin, Zheng, Zijian, Cai, Mingjie, Pedrycz, Witold, Xu, Zeshui
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	IEEE 01.08.2024
Témata:	<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
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