Abstract
Community detection is an important issue in the field of complex networks. Modularity is the most popular partition-based measure for community detection of networks represented as graphs. We present a hybrid algorithm mixing a dedicated crossover operator and a multi-level local optimization procedure. Experimental evaluations on a set of 11 well-known benchmark graphs show that the proposed algorithm attains easily all the current best solutions and even improves 6 of them in terms of maximum modularity. © 2012 Springer-Verlag.
Author supplied keywords
Cite
CITATION STYLE
Gach, O., & Hao, J. K. (2012). A memetic algorithm for community detection in complex networks. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7492 LNCS, pp. 327–336). https://doi.org/10.1007/978-3-642-32964-7_33
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
