Fuzzy Kernel Based Effective Clustering Techniques in Analyzing Heterogeneous Databases

S. R. Kannan; M. Siva; R. Devi; S. Ramathilagam; Mark Last

doi:10.1088/1742-6596/1344/1/012039

Fuzzy Kernel Based Effective Clustering Techniques in Analyzing Heterogeneous Databases

S. R. Kannan, M. Siva, R. Devi, S. Ramathilagam, Mark Last

Department of Software and Information Systems Engineering

Research output: Contribution to journal › Conference article › peer-review

Abstract

The aim of this paper is to introduce an effective fuzzy clustering technique based kernel function to find appropriate subgroups in heterogeneous databases. This paper introduces the effective fuzzy clustering that incorporates weighted bias field information, kernel distance, possibilistic memberships and fuzzy memberships into memberships equation and prototype equation. The effectiveness and efficiency of the proposed clustering techniques have been shown through the experimental results on benchmark heterogeneous databases.

Original language	English
Article number	012039
Journal	Journal of Physics: Conference Series
Volume	1344
Issue number	1
DOIs	https://doi.org/10.1088/1742-6596/1344/1/012039
State	Published - 31 Oct 2019
Event	International Conference on Recent Inventions and Innovations in Mathematical Sciences, ICRIIMS 2019 - Visakhapatnam, Andhra Pradesh, India Duration: 28 Feb 2019 → 1 Mar 2019

Keywords

Clustering
Fuzzy C-Means
Kernel Distance
heterogeneous databases

ASJC Scopus subject areas

General Physics and Astronomy

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10.1088/1742-6596/1344/1/012039

Cite this

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title = "Fuzzy Kernel Based Effective Clustering Techniques in Analyzing Heterogeneous Databases",

abstract = "The aim of this paper is to introduce an effective fuzzy clustering technique based kernel function to find appropriate subgroups in heterogeneous databases. This paper introduces the effective fuzzy clustering that incorporates weighted bias field information, kernel distance, possibilistic memberships and fuzzy memberships into memberships equation and prototype equation. The effectiveness and efficiency of the proposed clustering techniques have been shown through the experimental results on benchmark heterogeneous databases.",

keywords = "Clustering, Fuzzy C-Means, Kernel Distance, heterogeneous databases",

author = "Kannan, {S. R.} and M. Siva and R. Devi and S. Ramathilagam and Mark Last",

note = "Publisher Copyright: {\textcopyright} Published under licence by IOP Publishing Ltd.; International Conference on Recent Inventions and Innovations in Mathematical Sciences, ICRIIMS 2019 ; Conference date: 28-02-2019 Through 01-03-2019",

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AU - Kannan, S. R.

AU - Siva, M.

AU - Devi, R.

AU - Ramathilagam, S.

AU - Last, Mark

N1 - Publisher Copyright: © Published under licence by IOP Publishing Ltd.

PY - 2019/10/31

Y1 - 2019/10/31

N2 - The aim of this paper is to introduce an effective fuzzy clustering technique based kernel function to find appropriate subgroups in heterogeneous databases. This paper introduces the effective fuzzy clustering that incorporates weighted bias field information, kernel distance, possibilistic memberships and fuzzy memberships into memberships equation and prototype equation. The effectiveness and efficiency of the proposed clustering techniques have been shown through the experimental results on benchmark heterogeneous databases.

AB - The aim of this paper is to introduce an effective fuzzy clustering technique based kernel function to find appropriate subgroups in heterogeneous databases. This paper introduces the effective fuzzy clustering that incorporates weighted bias field information, kernel distance, possibilistic memberships and fuzzy memberships into memberships equation and prototype equation. The effectiveness and efficiency of the proposed clustering techniques have been shown through the experimental results on benchmark heterogeneous databases.

KW - Clustering

KW - Fuzzy C-Means

KW - Kernel Distance

KW - heterogeneous databases

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DO - 10.1088/1742-6596/1344/1/012039

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SN - 1742-6588

VL - 1344

JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

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T2 - International Conference on Recent Inventions and Innovations in Mathematical Sciences, ICRIIMS 2019

Y2 - 28 February 2019 through 1 March 2019

ER -

Fuzzy Kernel Based Effective Clustering Techniques in Analyzing Heterogeneous Databases

Abstract

Keywords

ASJC Scopus subject areas

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