Community detection in complex networks using extended compact genetic algorithm

Complex networks are often studied as graphs, and detecting communities in a complex network can be modeled as a seriously nonlinear optimization problem. Soft computing techniques have shown promising results for solving this problem. Extended compact genetic algorithm (ECGA) use statistical learning mechanism to build a probability distribution model of all individuals in a population, and then create new population by sampling individuals according to their probability distribution instead of using traditional crossover and mutation operations. ECGA has distinct advantages in solving nonlinear and variable-coupled optimization problems. This paper attempts to apply ECGA to explore community structure in complex networks. Experimental results based on the GN benchmark networks, the LFR benchmark networks, and six real-world complex networks, show that ECGA is more effective than some other algorithms of community detection.

[1]  Réka Albert,et al.  Near linear time algorithm to detect community structures in large-scale networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  Clara Pizzuti,et al.  GA-Net: A Genetic Algorithm for Community Detection in Social Networks , 2008, PPSN.

[3]  Martin Rosvall,et al.  Multilevel Compression of Random Walks on Networks Reveals Hierarchical Organization in Large Integrated Systems , 2010, PloS one.

[4]  Matthieu Latapy,et al.  Computing Communities in Large Networks Using Random Walks , 2004, J. Graph Algorithms Appl..

[5]  R. Guimerà,et al.  Functional cartography of complex metabolic networks , 2005, Nature.

[6]  M E J Newman,et al.  Finding and evaluating community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[7]  Zhewen Shi,et al.  PSO-Based Community Detection in Complex Networks , 2009, 2009 Second International Symposium on Knowledge Acquisition and Modeling.

[8]  R. Guimerà,et al.  Modularity from fluctuations in random graphs and complex networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[9]  G. Harik.  Linkage Learning via Probabilistic Modeling in the ECGA , 1999 .

[10]  F. Radicchi,et al.  Benchmark graphs for testing community detection algorithms. , 2008, Physical review. E, Statistical, nonlinear, and soft matter physics.

[11]  W. J. Conover,et al.  Practical Nonparametric Statistics , 1972 .

[12]  Bin Yang,et al.  Genetic Algorithm with Ensemble Learning for Detecting Community Structure in Complex Networks , 2009, 2009 Fourth International Conference on Computer Sciences and Convergence Information Technology.

[13]  Abhishek Verma,et al.  Scaling simple, compact and extended compact genetic algorithms using MapReduce , 2010 .

[14]  David E. Goldberg,et al.  The compact genetic algorithm , 1999, IEEE Trans. Evol. Comput..

[15]  M. Newman,et al.  Finding community structure in very large networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[16]  Haifeng Du,et al.  A genetic algorithm with local search strategy for improved detection of community structure , 2010, Complex..

[17]  A. Sima Etaner-Uyar,et al.  An efficient community detection method using parallel clique-finding ants , 2010, IEEE Congress on Evolutionary Computation.

[18]  Fernando G. Lobo,et al.  Extended Compact Genetic Algorithm in C , 1999 .

[19]  David E. Goldberg,et al.  Linkage Problem, Distribution Estimation, and Bayesian Networks , 2000, Evolutionary Computation.

[20]  M E J Newman,et al.  Modularity and community structure in networks. , 2006, Proceedings of the National Academy of Sciences of the United States of America.

[21]  Clara Pizzuti,et al.  A Multi-objective Genetic Algorithm for Community Detection in Networks , 2009, 2009 21st IEEE International Conference on Tools with Artificial Intelligence.

[22]  D. Goldberg,et al.  Modeling tournament selection with replacement using apparent added noise , 2001 .

[23]  T. Vicsek,et al.  Uncovering the overlapping community structure of complex networks in nature and society , 2005, Nature.

[24]  M. Newman,et al.  Finding community structure in networks using the eigenvectors of matrices. , 2006, Physical review. E, Statistical, nonlinear, and soft matter physics.

[25]  A. Arenas,et al.  Community detection in complex networks using extremal optimization. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[26]  Dayou Liu,et al.  Ant Colony Optimization with Markov Random Walk for Community Detection in Graphs , 2011, PAKDD.

[27]  Lars Kai Hansen,et al.  Deterministic modularity optimization , 2007 .

[28]  M. F. Fuller,et al.  Practical Nonparametric Statistics; Nonparametric Statistical Inference , 1973 .

[29]  Marko Bajec,et al.  Robust network community detection using balanced propagation , 2011, ArXiv.

[30]  S. Brenner,et al.  The structure of the nervous system of the nematode Caenorhabditis elegans. , 1986, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[31]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[32]  Lian Liu,et al.  Finding Closely Communicating Community Based on Ant Colony Clustering Model , 2010, 2010 International Conference on Artificial Intelligence and Computational Intelligence.

[33]  T. Murata,et al.  Advanced modularity-specialized label propagation algorithm for detecting communities in networks , 2009, 0910.1154.

[34]  W. Zachary,et al.  An Information Flow Model for Conflict and Fission in Small Groups , 1977, Journal of Anthropological Research.

[35]  Alok Singh,et al.  A new grouping genetic algorithm approach to the multiple traveling salesperson problem , 2008, Soft Comput..

[36]  Pablo M. Gleiser,et al.  Community Structure in Jazz , 2003, Adv. Complex Syst..

[37]  Cristopher Moore,et al.  Structural Inference of Hierarchies in Networks , 2006, SNA@ICML.

[38]  Marko Bajec,et al.  Unfolding communities in large complex networks: Combining defensive and offensive label propagation for core extraction , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[39]  Lin Yanping,et al.  Web community detection model using particle swarm optimization , 2008, 2008 IEEE Congress on Evolutionary Computation (IEEE World Congress on Computational Intelligence).

[40]  David Lusseau,et al.  The emergent properties of a dolphin social network , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[41]  Haluk Bingol,et al.  Community Detection in Complex Networks Using Genetic Algorithms , 2006, 0711.0491.

[42]  Martin Rosvall,et al.  Maps of random walks on complex networks reveal community structure , 2007, Proceedings of the National Academy of Sciences.

[43]  Edoardo M. Airoldi,et al.  Statistical Network Analysis: Models, Issues, and New Directions - ICML 2006 Workshop on Statistical Network Analysis, Pittsburgh, PA, USA, June 29, 2006, Revised Selected Papers , 2007, SNA@ICML.

[44]  M. Newman,et al.  Hierarchical structure and the prediction of missing links in networks , 2008, Nature.

[45]  Leon Danon,et al.  Comparing community structure identification , 2005, cond-mat/0505245.

[46]  Martin Rosvall,et al.  An information-theoretic framework for resolving community structure in complex networks , 2007, Proceedings of the National Academy of Sciences.

[47]  David Kempe,et al.  Modularity-maximizing graph communities via mathematical programming , 2007, 0710.2533.

[48]  D. Goldberg,et al.  ClusterMI: Building Probabilistic Models Using Hierarchical Clustering and Mutual Information , 2010 .

[49]  Santo Fortunato,et al.  Community detection in graphs , 2009, ArXiv.

[50]  Ivo Everts,et al.  Extended Compact Genetic Algorithm , 2004 .

[51]  Carl T. Bergstrom,et al.  Mapping Change in Large Networks , 2008, PloS one.

[52]  Yanqing Zhang,et al.  A genetic algorithm-based method for feature subset selection , 2008, Soft Comput..

[53]  M. Newman,et al.  Robustness of community structure in networks. , 2007, Physical review. E, Statistical, nonlinear, and soft matter physics.