Title: A novel complex community network division algorithm with multi-gene families encoding

Authors: Kangshun Li; Guihua Chen

Addresses: College of Information, South China Agricultural University, Guangzhou 510642, China; School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China ' School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou 341000, China

Abstract: To overcome the drawbacks of traditional complex community network division algorithms, such as low accuracy, high time complexity and easily being trapped into local optimum, a novel complex community network division algorithm is proposed by using Multi-Gene Families (MGF). The proposed approach first encodes the node ID and the community type into two different MGFs, respectively, and then encodes the relationship of the two MGFs into the chromosome through a mapping function. Moreover, in order to prevent premature and speed up convergence, the elite migration strategy is utilised throughout the evolution process, such as gene selection, chromosome crossover, chromosome inversion, restricted permutation. The experiments and analyses show that our approach is better than the traditional evolutionary algorithm in terms of efficiency and accuracy.

Keywords: complex networks; community structure division; community division; MGF; multi-gene families; GEP; gene expression programming; elite migration strategy.

DOI: 10.1504/IJWMC.2013.057577

International Journal of Wireless and Mobile Computing, 2013 Vol.6 No.6, pp.621 - 627

Received: 23 May 2013
Accepted: 03 Jul 2013

Published online: 12 Nov 2013 *

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