Open AccessCommon strategy to improve community detection performance based on the nodes’ property
Author(s) -
Du Wei,
He Xiaochen
Publication year - 2017
Publication title -
caai transactions on intelligence technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.613
H-Index - 15
ISSN - 2468-2322
DOI - 10.1049/trit.2017.0003
Subject(s) - modularity (biology) , community structure , node (physics) , computer science , sign (mathematics) , property (philosophy) , clique percolation method , complex network , data mining , order (exchange) , value (mathematics) , engineering , machine learning , mathematics , world wide web , business , mathematical analysis , philosophy , genetics , structural engineering , epistemology , finance , combinatorics , biology
Improving the community detection algorithm is of great importance. The authors propose a novel method based on the nodes’ property in order to detect the community structure. Given a detected community structure, in which nodes have their community signals, the value of the modularity can be changed if a node's community sign change to other communities’ signs. Accordingly, the new method readjusts the affiliation between a node and its community in order to raise the modularity value. Experimental results of the detection for a list of open‐source networks show that the proposed algorithm can detect better community structure than classic methodologies based on modularity.