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2013 | OriginalPaper | Chapter

25. Complex Network Community Detection Algorithm Based on Genetic Algorithm

Authors : Yun Li, Gang Liu, Song-yang Lao

Published in: The 19th International Conference on Industrial Engineering and Engineering Management

Publisher: Springer Berlin Heidelberg

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Abstract

For the problem of complex network community detection, propose a new algorithm based on genetic algorithm to solve it. This algorithm sets network modularity function as target function and fitness function, uses matrix encoding to describe individuals, and generates initial population using nodes similarity. The crossover operation is based on the quality of individuals’ genes, in this process, all nodes that weren’t partitioned into any communities make up a new one together, and the nodes that were partitioned into more than one community are placed into the community to which most of their neighbors belong. The mutation operation is non-uniform, which splits the mutation gene into two new genes or fuses it into the others randomly. The experiment proved that this algorithm could effectively detect communities in complex networks.

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Metadata
Title
Complex Network Community Detection Algorithm Based on Genetic Algorithm
Authors
Yun Li
Gang Liu
Song-yang Lao
Copyright Year
2013
Publisher
Springer Berlin Heidelberg
DOI
https://doi.org/10.1007/978-3-642-37270-4_25