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

Issue title: FUZZYSS'2011: 2nd International Fuzzy Systems Symposium

Article type: Research Article

Authors: Ulutagay, Gözde | Nasibov, Efendi^;

Affiliations: Department of Industrial Engineering, Izmir University, Izmir, Turkey | Department of Computer Science, Dokuz Eylül University, Izmir, Turkey | Institute of Cybernetics, Azerbaijan National Academy of Sciences, Baku, Azerbaijan

Note: [] Corresponding author. Gözde Ulutagay, Department of Industrial Engineering, Izmir University, Izmir, Turkey. E-mails: gozde.ulutagay@izmir.edu.tr (Gözde Ulutagay), efendi.nasibov@deu.edu.tr (Efendi Nasibov).

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.

Keywords: Neighborhood-based cluster analysis, spatial data, DBSCAN, FDBSCAN, LDBSCAN, NRFJP, Bifurcated FJP, FN-DBSCAN, SDBSCAN, Scalable FN-DBSCAN

DOI: 10.3233/IFS-2012-0519

Journal: Journal of Intelligent & Fuzzy Systems, vol. 23, no. 6, pp. 271-281, 2012