Fuzzy Kernel Based Effective Clustering Techniques in Analyzing Heterogeneous Databases

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

Research output: Contribution to journalConference articlepeer-review


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 languageEnglish
Article number012039
JournalJournal of Physics: Conference Series
Issue number1
StatePublished - 31 Oct 2019
EventInternational Conference on Recent Inventions and Innovations in Mathematical Sciences, ICRIIMS 2019 - Visakhapatnam, Andhra Pradesh, India
Duration: 28 Feb 20191 Mar 2019


  • Clustering
  • Fuzzy C-Means
  • Kernel Distance
  • heterogeneous databases

ASJC Scopus subject areas

  • Physics and Astronomy (all)


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