A better strategy of discovering link-pattern based communities by classical clustering methods

Chen Yi Lin, Jia Ling Koh, Arbee L.P. Chen

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

5 Citations (Scopus)

Abstract

The definition of a community in social networks varies with applications. To generalize different types of communities, the concept of linkpattern based community was proposed in a previous study to group nodes into communities, where the nodes in a community have similar intra-community and inter-community interaction behaviors. In this paper, by defining centroid of a community, a distance function is provided to measure the similarity between the link pattern of a node and the centroid of a community. The problem of discovering link-pattern based communities is transformed into a data clustering problem on nodes for minimizing a given objective function. By extending the partitioning methods of cluster analysis, two algorithms named G-LPC and KM-LPC are proposed to solve the problem. The experiment results show that KM-LPC outperforms the previous work on the efficiency, the memory utilization, and the clustering result. Besides, G-LPC achieves the best result approaching the optimal solution.

Original languageEnglish
Title of host publicationAdvances in Knowledge Discovery and Data Mining - 14th Pacific-Asia Conference, PAKDD 2010, Proceedings
Pages56-67
Number of pages12
EditionPART 1
DOIs
Publication statusPublished - 2010 Dec 1
Event14th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2010 - Hyderabad, India
Duration: 2010 Jun 212010 Jun 24

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6118 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other14th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2010
CountryIndia
CityHyderabad
Period10/6/2110/6/24

Keywords

  • Clustering algorithms
  • Link-pattern based community
  • Social network

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'A better strategy of discovering link-pattern based communities by classical clustering methods'. Together they form a unique fingerprint.

Cite this