Fuzzy and crisp clustering methods based on the neighborhood concept: A comprehensive review

Ulutagay G., Nasibov E.

JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, vol.23, no.6, pp.271-281, 2012 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 23 Issue: 6
  • Publication Date: 2012
  • Doi Number: 10.3233/ifs-2012-0519
  • Journal Name: JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.271-281
  • Keywords: Neighborhood-based cluster analysis, spatial data, DBSCAN, FDBSCAN, LDBSCAN, NRFJP, Bifurcated FJP, FN-DBSCAN, SDBSCAN, Scalable FN-DBSCAN, ALGORITHM
  • Dokuz Eylül University Affiliated: Yes

Abstract

The aim of this paper has twofold: i) to explore the fundamental concepts and methods of neighborhood-based cluster analysis with its roots in statistics and decision theory, ii) to provide a compact tool for researchers. Since DBSCAN is the first method which uses the concept of neighborhood and it has many successors, we started our discussion by exploring it. Then we compared some of the successors of DBSCAN algorithm and other crisp and fuzzy methods on the basis of neighborhood strategy.