A Social Network Clustering Analysis Algorithm Based on Memetic Algorithm and Relationship Learning
SUN Yifei1a, YAO Ruoxia1b, JIAO Licheng2
1. a.School of Physics and Information Technology, b.School of Computer Science, Shaanxi Normal University, Xi’an 710119; 2. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education,Xidian University, Xi’an 710071
Abstract：In social networks, the property of society has not been fully exploited. Meanwhile, learning ability for network structure optimization is weak. So a new Memetic Relationship Learning Algorithm (MRLA) has been proposed. This paper studied the fundamentals and basic procedure of MRLA, and effectively utilized the social attribute information. The new algorithm integrated the accuracy of Memetic computation and the quickness of social relational learning. The experimental results of three real-world web data sets show the validity and feasibility of the proposed algorithms.
孙奕菲, 姚若侠, 焦李成. 基于Memetic算法和关联学习的社会网络聚类分析[J]. 复杂系统与复杂性科学, 2017, 14(2): 89-96.
SUN Yifei, YAO Ruoxia, JIAO Licheng. A Social Network Clustering Analysis Algorithm Based on Memetic Algorithm and Relationship Learning[J]. Complex Systems and Complexity Science, 2017, 14(2): 89-96.
[1] Newman M E J. Detecting community structure in networks[J].The European Physical Journal B-Condensed Matter and Complex Systems, 2004, 38(2): 321-330.
[2] Lancichinetti A, Fortunato S. Community detection algorithms: a comparative analysis[J].Physical review E, 2009, 80(5): 056117.
[3] Fortunato S. Community detection in graphs[J].Physics Reports, 2010, 486(3): 75-174.
[4] 解, 汪小帆. 复杂网络中的社区结构分析算法研究综述[J].复杂系统与复杂性科学. 2005, 2(3): 1-12.
Xie Zhou, Wang Xiaofan. An overview of algorithms for analyzing community structure in complex networks[J].Complex systems and complexity science, 2005, 2(3): 1-12.
[5] 李晓佳, 张鹏, 狄增如,等.复杂网络中的社区结构. 复杂系统与复杂性科学. 2008, 5(3): 19-42.
Li Xiaojia, Zhang Peng, Di Zengru, et al. Community structure in complex networks[J].Complex systems and complexity science, 2008, 5(3): 19-42.
[6] Li D Y, Xiao L, Han Y, et al. Network thinking and network intelligence[J].Web Intelligence Meets Brain Informatics. Springer, 2007, 36-58.
[7] Moscato P. On evolution, search, optimization, genetic algorithms and martial arts: towards memeticalgorithms[J].Caltech concurrent computation program, C3P Report, 1989, 826: 1989.
[8] Wang S, Wang L. An estimation of distribution algorithm-based memeticalgorithm for the distributed assembly permutation flow-shop scheduling problem[J].IEEE Transactions on System, Man, Cybernetics, 2016, 46(1):139-149.
[9] Lazer D, Pentland A, Adamic L, et al. Computational social science[J].Science,2009, 323(1):721-723.
[10] Giles J. Computational social science: making the links[J].Nature, 2012,488(7412):448-450.
[11] Ong Y S, Lim M H, Chen X. Research frontier-memetic computation—past, present & future[J].IEEE Computational Intelligence Magazine, 2010, 5(2): 24.
[12] Cai Q, Ma L, Gong M, et al. A survey on network community detection based on evolutionary computation[J].International Journal of Bio-Inspired Computation, 2016, 8(2): 84-98.
[13] Granovetter M S. The strength of weak ties[J].American Journal of Sociology, 1973: 1360-1380.
[14] Friedmann J. The world city hypothesis[J].Development and Change, 1986, 17(1): 69-83.
[15] Guest L. Review of the people′s choice: how the voter makes up his mind in a presidential campaign.[J].American Journal of Sociology, 1946, 77(51):177-186.
[16] Lusseau D, Schneider K, Boisseau O J, et al. The bottlenose dolphin community of doubtful sound features a large proportion of long-lasting associations[J].Behavioral Ecology and Sociobiology, 2003, 54(4): 396-405.
[17] Zachary W W. An information flow model for conflict and fission in small groups[J].Journal of Anthropological Research, 1977: 452-473.
[18] Girvan M, Newman M E J. Community structure in social and biological networks[J].Proceedings of the National Academy of Sciences, 2002, 99(12): 7821-7826.
, 汪小帆. 复杂网络中的社区结构分析算法研究综述[J].复杂系统与复杂性科学. 2005, 2(3): 1-12.