Graph clustering using distance-k cliques software demonstration

Jubin Edachery, Arunabha Sen, Franz J. Brandenburg

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

32 Citations (Scopus)

Abstract

Identifying the natural clusters of nodes in a graph and treating them as supernodes or metanodes for a higher level graph (or an abstract graph) is a technique used for the reduction of visual complexity of graphs with a large number of nodes. In this paper we report on the implementation of a clustering algorithm based on the idea of distance-k cliques, a generalization of the idea of the cliques in graphs. The performance of the clustering algorithm on some large graphs obtained from the archives of Bell Laboratories is presented.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages98-106
Number of pages9
Volume1731
ISBN (Print)3540669043, 9783540669043
DOIs
StatePublished - 1999
Event7th International Symposium on Graph Drawing, GD 1999 - Prague, Czech Republic
Duration: Sep 15 1999Sep 19 1999

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1731
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other7th International Symposium on Graph Drawing, GD 1999
CountryCzech Republic
CityPrague
Period9/15/999/19/99

Fingerprint

Graph Clustering
Clique
Clustering algorithms
Demonstrations
Software
Graph in graph theory
Clustering Algorithm
Vertex of a graph

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Edachery, J., Sen, A., & Brandenburg, F. J. (1999). Graph clustering using distance-k cliques software demonstration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1731, pp. 98-106). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1731). Springer Verlag. https://doi.org/10.1007/3-540-46648-7_10

Graph clustering using distance-k cliques software demonstration. / Edachery, Jubin; Sen, Arunabha; Brandenburg, Franz J.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1731 Springer Verlag, 1999. p. 98-106 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1731).

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

Edachery, J, Sen, A & Brandenburg, FJ 1999, Graph clustering using distance-k cliques software demonstration. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 1731, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 1731, Springer Verlag, pp. 98-106, 7th International Symposium on Graph Drawing, GD 1999, Prague, Czech Republic, 9/15/99. https://doi.org/10.1007/3-540-46648-7_10
Edachery J, Sen A, Brandenburg FJ. Graph clustering using distance-k cliques software demonstration. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1731. Springer Verlag. 1999. p. 98-106. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/3-540-46648-7_10
Edachery, Jubin ; Sen, Arunabha ; Brandenburg, Franz J. / Graph clustering using distance-k cliques software demonstration. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 1731 Springer Verlag, 1999. pp. 98-106 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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