Finding fuzzy communities in directed networks

Kun Zhao, Shao Wu Zhang, Quan Pan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

To comprehend the directed networks in a fuzzy view, we introduce a new matrix decomposition approach that reveals overlapping community structure in weighted and directed networks. This method decomposes a directed network into modules by optimally decomposing the asymmetric feature matrix of the directed network into two matrices separately representing the closeness degree from node to community and the closeness degree from community to node. Their combined result uncovers the community structures in a fuzzy sense in the directed networks. The illustrations on an artificial network and a word association network give reasonable results.

Original languageEnglish
Title of host publicationProceedings of the 6th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Workshop, ANNIIP 2010, in Conjunction with ICINCO 2010
Pages3-12
Number of pages10
StatePublished - 2010
Event6th International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2010, in Conjunction with ICINCO 2010 - Funchal, Portugal
Duration: 17 Jun 201018 Jun 2010

Publication series

NameProceedings of the 6th International Workshop on Artificial Neural Networks and Intelligent Information Processing - Workshop, ANNIIP 2010, in Conjunction with ICINCO 2010

Conference

Conference6th International Workshop on Artificial Neural Networks and Intelligent Information Processing, ANNIIP 2010, in Conjunction with ICINCO 2010
Country/TerritoryPortugal
CityFunchal
Period17/06/1018/06/10

Fingerprint

Dive into the research topics of 'Finding fuzzy communities in directed networks'. Together they form a unique fingerprint.

Cite this