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אקדמי בכיר

Fuzzy Kernel Based Effective Clustering Techniques in Analyzing Heterogeneous Databases

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

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.

שפת פרסום אנגלית
כתב עת Journal of Physics: Conference Series
כרך 1344
נושא מספר 1
סטטוס פרסום פורסם - 31.10.2019
מספר מאמר 012039

Keywords

Clustering
Fuzzy C-Means
Kernel Distance
heterogeneous databases

ASJC Scopus subject areas

General Physics and Astronomy
קבצים וקישורים אחרים
Link to publication in Scopus