MA-Net: A reliable memetic algorithm for community detection by modularity optimization

The information that can be transformed in knowledge from data in challenging real-world problems follows the accelerated rate of the advancement of technology in many different fields from biology to sociology. Complex networks are a useful representation of many problems in these domains One of the most important and challenging problems in network analysis lies in detecting community structures. This area of algorithmic research has attracted great attention due to its possible application in many fields. In this study we propose the MA-Net, memetic algorithm to detect communities in network by optimizing modularity value which is fast and reliable in the sense that it consistently produces sound solutions. Experiments using well-known real-world benchmark networks indicate that in comparison with other state-of-the-art algorithms, MA-Net has an outstanding performance on detecting communities.

[1]  M. Newman,et al.  Finding community structure in very large networks. , 2004, 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]  Xiao Zhang,et al.  Community detection using parallel genetic algorithms , 2012, 2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI).

[4]  David A. Bader,et al.  Scalable Multi-threaded Community Detection in Social Networks , 2012, 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum.

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

[6]  Yasuhiro Fujiwara,et al.  Fast Algorithm for Modularity-Based Graph Clustering , 2013, AAAI.

[7]  Pablo Moscato,et al.  Handbook of Memetic Algorithms , 2011, Studies in Computational Intelligence.

[8]  Benjamin H. Good,et al.  Performance of modularity maximization in practical contexts. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[9]  Jean-Loup Guillaume,et al.  Fast unfolding of communities in large networks , 2008, 0803.0476.

[10]  David A. Bader,et al.  Parallel Community Detection for Massive Graphs , 2011, PPAM.

[11]  M. Newman.  Analysis of weighted networks. , 2004, Physical review. E, Statistical, nonlinear, and soft matter physics.

[12]  Sean R. Collins,et al.  Global landscape of protein complexes in the yeast Saccharomyces cerevisiae , 2006, Nature.

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

[14]  P. Bork,et al.  Proteome survey reveals modularity of the yeast cell machinery , 2006, Nature.

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

[16]  S. Fortunato,et al.  Resolution limit in community detection , 2006, Proceedings of the National Academy of Sciences.

[17]  Luonan Chen,et al.  Quantitative function for community detection. , 2008 .

[18]  P. Kollock,et al.  Communities in Cyberspace , 2002 .

[19]  M. Barber,et al.  Detecting network communities by propagating labels under constraints. , 2009, Physical review. E, Statistical, nonlinear, and soft matter physics.

[20]  P. Moscato,et al.  A Data-Driven Approach to Reverse Engineering Customer Engagement Models: Towards Functional Constructs , 2014, PloS one.

[21]  David A. Bader,et al.  Tracking Structure of Streaming Social Networks , 2011, 2011 IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum.

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

[23]  Jie Liu,et al.  Multi-level learning based memetic algorithm for community detection , 2014, Appl. Soft Comput..

[24]  Jianwu Li,et al.  Community detection in complex networks using extended compact genetic algorithm , 2012, Soft Computing.

[25]  Jooyoung Lee,et al.  Hidden Information Revealed by Optimal Community Structure from a Protein-Complex Bipartite Network Improves Protein Function Prediction , 2013, PloS one.

[26]  Francisco Herrera,et al.  A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms , 2011, Swarm Evol. Comput..

[27]  Maoguo Gong,et al.  Memetic algorithm for community detection in networks. , 2011, Physical review. E, Statistical, nonlinear, and soft matter physics.

[28]  Robert E. Park,et al.  Physics and Society , 1940 .

[29]  Jian Liu,et al.  Detecting community structure in complex networks using simulated annealing with k-means algorithms , 2010 .

[30]  Sergey Brin,et al.  The Anatomy of a Large-Scale Hypertextual Web Search Engine , 1998, Comput. Networks.

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

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

[33]  Dayou Liu,et al.  Genetic Algorithm with a Local Search Strategy for Discovering Communities in Complex Networks , 2013, Int. J. Comput. Intell. Syst..

[34]  M E J Newman,et al.  Fast algorithm for detecting community structure in networks. , 2003, Physical review. E, Statistical, nonlinear, and soft matter physics.

[35]  D. Lusseau,et al.  The bottlenose dolphin community of Doubtful Sound features a large proportion of long-lasting associations , 2003, Behavioral Ecology and Sociobiology.

[36]  U. Brandes,et al.  Maximizing Modularity is hard , 2006, physics/0608255.

[37]  Jin-Kao Hao,et al.  A Memetic Algorithm for Community Detection in Complex Networks , 2012, PPSN.

[38]  Ulrik Brandes,et al.  On Modularity Clustering , 2008, IEEE Transactions on Knowledge and Data Engineering.

[39]  Vincenzo Cutello,et al.  Parallel Problem Solving from Nature - PPSN XII , 2012, Lecture Notes in Computer Science.

[40]  Sune Lehmann,et al.  Link communities reveal multiscale complexity in networks , 2009, Nature.

[41]  Andreas Noack,et al.  Multilevel local search algorithms for modularity clustering , 2011, JEAL.

[42]  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.

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

[44]  Clara Pizzuti,et al.  A Multiobjective Genetic Algorithm to Find Communities in Complex Networks , 2012, IEEE Transactions on Evolutionary Computation.

[45]  Qingfu Zhang,et al.  Community detection in networks by using multiobjective evolutionary algorithm with decomposition , 2012 .

[46]  Xiang-Sun Zhang,et al.  Erratum: Quantitative function for community detection [Phys. Rev. E 77, 036109 (2008)] , 2015 .

[47]  Cornelis J Stam,et al.  Graph theoretical analysis of complex networks in the brain , 2007, Nonlinear biomedical physics.

[48]  Jacek M. Zurada,et al.  Swarm and Evolutionary Computation , 2012, Lecture Notes in Computer Science.

[49]  Lazaros G. Papageorgiou,et al.  Finding community structures in complex networks using mixed integer optimisation , 2007 .

[50]  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.

[51]  Yangyang Li,et al.  An improved memetic algorithm for community detection in complex networks , 2012, 2012 IEEE Congress on Evolutionary Computation.

[52]  Steven P Gross,et al.  Modularity optimization by conformational space annealing. , 2012, Physical review. E, Statistical, nonlinear, and soft matter physics.

[53]  Solon P. Pissis,et al.  Parallelising the Computation of Minimal Absent Words , 2015, PPAM.

[54]  Ludo Waltman,et al.  A smart local moving algorithm for large-scale modularity-based community detection , 2013, The European Physical Journal B.

[55]  P. Hansen,et al.  Column generation algorithms for exact modularity maximization in networks. , 2010, Physical review. E, Statistical, nonlinear, and soft matter physics.

[56]  O. Sporns,et al.  Complex brain networks: graph theoretical analysis of structural and functional systems , 2009, Nature Reviews Neuroscience.