Improvement of Jarvis-Patrick clustering based on fuzzy similarity

Agnes Vathy-Fogarassy, Attila Kiss, J. Abonyi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Different clustering algorithms are based on different similarity or distance measures (e.g. Euclidian distance, Minkowsky distance, Jackard coefficient, etc.). Jarvis-Patrick clustering method utilizes the number of the common neighbors of the k-nearest neighbors of objects to disclose the clusters. The main drawback of this algorithm is that its parameters determine a too crisp cutting criterion, hence it is difficult to determine a good parameter set. In this paper we give an extension of the similarity measure of the Jarvis-Patrick algorithm. This extension is carried out in the following two ways: (i) fuzzyfication of one of the parameters, and (ii) spreading of the scope of the other parameter. The suggested fuzzy similarity measure can be applied in various forms, in different clustering and visualization techniques (e.g. hierarchical clustering, MDS, VAT). In this paper we give some application examples to illustrate the efficiency of the use of the proposed fuzzy similarity measure in clustering. These examples show that the proposed fuzzy similarity measure based clustering techniques are able to detect clusters with different sizes, shapes and densities. It is also shown that the outliers are also detectable by the proposed measure.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages195-202
Number of pages8
Volume4578 LNAI
Publication statusPublished - 2007
Event7th International Workshop on Fuzzy Logic and Applications, WILF 2007 - Camogli, Italy
Duration: Jul 7 2007Jul 10 2007

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4578 LNAI
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other7th International Workshop on Fuzzy Logic and Applications, WILF 2007
CountryItaly
CityCamogli
Period7/7/077/10/07

Fingerprint

Similarity Measure
Cluster Analysis
Clustering
Fuzzy Measure
Clustering algorithms
Visualization
Hierarchical Clustering
Distance Measure
Clustering Methods
Outlier
Clustering Algorithm
Nearest Neighbor
Similarity
Coefficient

Keywords

  • Fuzzy similarity measure
  • JarvisPatrick clustering
  • MDS
  • Neighborhood relation
  • VAT

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Vathy-Fogarassy, A., Kiss, A., & Abonyi, J. (2007). Improvement of Jarvis-Patrick clustering based on fuzzy similarity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4578 LNAI, pp. 195-202). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4578 LNAI).

Improvement of Jarvis-Patrick clustering based on fuzzy similarity. / Vathy-Fogarassy, Agnes; Kiss, Attila; Abonyi, J.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4578 LNAI 2007. p. 195-202 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4578 LNAI).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Vathy-Fogarassy, A, Kiss, A & Abonyi, J 2007, Improvement of Jarvis-Patrick clustering based on fuzzy similarity. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4578 LNAI, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4578 LNAI, pp. 195-202, 7th International Workshop on Fuzzy Logic and Applications, WILF 2007, Camogli, Italy, 7/7/07.
Vathy-Fogarassy A, Kiss A, Abonyi J. Improvement of Jarvis-Patrick clustering based on fuzzy similarity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4578 LNAI. 2007. p. 195-202. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Vathy-Fogarassy, Agnes ; Kiss, Attila ; Abonyi, J. / Improvement of Jarvis-Patrick clustering based on fuzzy similarity. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4578 LNAI 2007. pp. 195-202 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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