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Inter-dimensional fuzzy clustering

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Yong ShiAuthors Info & Claims

ACMSE '10: Proceedings of the 48th annual ACM Southeast Conference

Article No.: 89, Pages 1 - 2

https://doi.org/10.1145/1900008.1900127

Published: 15 April 2010 Publication History

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Abstract

In this paper, we present our research on detecting clusters for multi-dimensional data using fuzzy concepts. Cluster analysis is an important sub-field in data mining. Many algorithms have been designed to detect clusters. However, it is difficult to analyze the inter-relationship among different dimensions. In this paper, we propose a novel approach to analyze and quantify the inter-relationship among correlated dimensions using the Fuzzy concept. A fuzzy concept is a concept of which the content, value, or boundaries of application can vary according to context or conditions, instead of being fixed once and for all. We apply the Fuzzy concept to help improve the clustering process.

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Yassine SNajib EFatima L(2019)Dynamic Cluster Head Selection Method for Wireless Sensor Network for Agricultural Application of Internet of Things based Fuzzy C-means Clustering Algorithm2019 7th Mediterranean Congress of Telecommunications (CMT)10.1109/CMT.2019.8931313(1-9)Online publication date: Oct-2019
https://doi.org/10.1109/CMT.2019.8931313

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Published In

ACMSE '10: Proceedings of the 48th annual ACM Southeast Conference

April 2010

488 pages

ISBN:9781450300643

DOI:10.1145/1900008

Conference Chair:
H. Conrad Cunningham
University of Mississippi
,
Program Chairs:
Paul Ruth,
Nicholas A. Kraft

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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Published: 15 April 2010

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ACM SE '10: ACM Southeast Regional Conference

April 15 - 17, 2010

Mississippi, Oxford

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ACMSE '10 Paper Acceptance Rate 48 of 94 submissions, 51%;

Overall Acceptance Rate 502 of 1,023 submissions, 49%

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Yassine SNajib EFatima L(2019)Dynamic Cluster Head Selection Method for Wireless Sensor Network for Agricultural Application of Internet of Things based Fuzzy C-means Clustering Algorithm2019 7th Mediterranean Congress of Telecommunications (CMT)10.1109/CMT.2019.8931313(1-9)Online publication date: Oct-2019
https://doi.org/10.1109/CMT.2019.8931313

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Bias-correction fuzzy clustering algorithms

New Inter-Cluster Proximity Index for Fuzzy c-Means Clustering

Kernel-based fuzzy clustering and fuzzy clustering: A comparative experimental study

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