A Neighborhood-Impact Based Community Detection Algorithm via Discrete PSO

The paper addresses particle swarm optimization (PSO) into community detection problem, and an algorithm based on new label strategy is proposed. In contrast with other label propagation strategies, the main contribution of this paper is to design the definition of the impact of node and take it int...

Full description

Saved in:
Bibliographic Details
Published in:Mathematical problems in engineering 2016-01, Vol.2016 (2016), p.1-15
Main Authors: Zhou, Dongqing, Wang, Xing
Format: Article
Language:English
Subjects:
Algorithms
Clustering
Communities
Computer science
Density
Labels
Mathematical analysis
Methods
Modularity
Networks
Optimization
Particle swarm optimization
Strategy
Studies
Swarm intelligence
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The paper addresses particle swarm optimization (PSO) into community detection problem, and an algorithm based on new label strategy is proposed. In contrast with other label propagation strategies, the main contribution of this paper is to design the definition of the impact of node and take it into use. Special initialization and update approaches based on it are designed in order to make full use of it. Experiments on synthetic and real-life networks show the effectiveness of proposed strategy. Furthermore, this strategy is extended to signed networks, and the corresponding objective function which is called modularity density is modified to be used in signed networks. Experiments on real-life networks also demonstrate that it is an efficacious way to solve community detection problem.
ISSN:1024-123X
1563-5147
DOI:10.1155/2016/3790590