[Objective] This paper proposed a fuzzy community partition algorithm based on node vector representation,aiming to solve the problems of poor efficiency and accuracy of existing fuzzy overlapping community partition algorithms. [Methods] Firstly, the random walk strategy guided by node importance is used to generate the walk sequence, and then the skip-gram model is used to train the node vector. Then, the Gaussian mixture model is introduced into the community partition to realize the multi peak node data fitting. Finally, the optimal number of communities is obtained by maximizing the modularity. [Results] Compared with the classical community detection method, the EQ values of the algorithm on the real network jazz and artificial network N1 (mu = 0.5) are increased by 7.0% and 9.7% respectively, which can more accurately detect the community structure in the network. [Limitations] In the vector representation learning, only the topological structure information of complex network is considered, while the node attribute information and edge label information are ignored. [Conclusions] The fuzzy overlapping community detection algorithm based on node vector representation can effectively complete the community division task of complex network.
( Xiao Jing, Zhang Yongjian, Xu Xiaoke. Research Progress of Fuzzy Overlapping Community Detection in Complex Networks[J]. Complex Systems and Complexity Science, 2017,14(3):8-29.)
[3]
Mikolov T, Sutskever I, Chen K, et al. Distributed Representations of Words and Phrases and Their Compositionality[C]// Proceedings of Advances in Neural Information Processing Systems. 2013: 3111-3119.
[4]
Perozzi B, Alrfou R, Skiena S. DeepWalk: Online Learning of Social Representations[C]// Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Detection and Data Mining. 2014: 701-710.
[5]
Bezdek J C, Ehrlich R, Full W. FCM: The Fuzzy c-Means Clustering Algorithm[J]. Computers & Geoences, 1984,10(2/3):191-203.
[6]
Yu S X, Shi J. Multiclass Spectral Clustering[C]// Proceedings of the 9th IEEE International Conference on Computer Vision. IEEE Computer Society, 2003.
[7]
Zhang S, Wang R S, Zhang X S. Identification of Overlapping Community Structure in Complex Networks Using Fuzzy c-means Clustering[J]. Physica A: Statistical Mechanics and Its Applications, 2007,374(1):483-490.
doi: 10.1016/j.physa.2006.07.023
[8]
Wang W J, Liu D, Liu X, et al. Fuzzy Overlapping Community Detection Based on Local Random Walk and Multidimensional Scaling[J]. Physica A: Statistical Mechanics and Its Applications, 2013,392(24):6578-6586.
doi: 10.1016/j.physa.2013.08.028
( Sun Weiyan, Peng Zhiming, Li Jianbo. Community Detection Algorithm Based on Particle Swarm Optimization and Fuzzy Clustering[J]. Journal of Chongqing University of Posts and Telecommunications (Natural Science Edition), 2015,27(05):660-666.)
( Fu Rao, Meng Fanrong, Xing Yan. Overlapping Community Discovery Algorithm Based on Node Importance and Similarity[J]. Computer Engineering, 2018,44(9):192-198.)
( Wang Xiaofeng, Liu Gongshen, Li Jianhua. Multiresolution Community Detection Based on Fuzzy Clustering[J]. Journal of Electronics & Information Technology, 2017,39(9):2033-2039.)
( Duan Zhongxiang. Automatic Detection and Simulation of Complex Network Fuzzy Overlapping Community Structure[J]. Computer Simulation, 2020,37(6):352-356.)
[13]
Lee D D, Seung H S. Learning the Parts of Objects by Non-Negative Matrix Factorization[J]. Nature, 1999,401:788-791.
pmid: 10548103
[14]
Zhang S H, Wang R S, Zhang X S. Uncovering Fuzzy Community Structure in Complex Networks[J]. Physical Review E Statal Nonlinear & Soft Matter Physics, 2007,76(4):046103.
[15]
Psorakis I, Roberts S, Ebden M, et al. Overlapping Community Detection Using Bayesian Non-Negative Matrix Factorization[J]. Physical Review E Statal Nonlinear & Soft Matter Physics, 2011,83(6):066114.
( Li Yuxiang, Li Bicheng, Guo Zhigang. Research on Overlapping Community Detection in Networks Using Non-negative Matrix Factorization[J]. Journal of System Simulation, 2014,26(3):643-649.)
[17]
Ye F H, Chen C, Zheng Z B, et al. Discrete Overlapping Community Detection with Pseudo Supervision[C]// Proceedings of 2019 IEEE International Conference on Data Mining (ICDM). IEEE, 2020.
[18]
Gregory S. Finding Overlapping Communities in Networks by Label Propagation[J]. New Journal of Physics, 2009,12(10):2011-2024.
( Liu Shichao, Zhu Fuxi, Gan Lin. A Label-Propagation-Probability-Based Algorithm for Overlapping Community Detection[J]. Chinese Journal of Computers, 2016,39(4):717-729.)
( Deng Kun, Li Wenping, Chen Li, et al. A Novel Algorithm for Overlapping Community Detection Based on Label Propagation in Complex Networks[J]. Control and Decision, 2020,35(11):2733-2742.)
( Chen Junyu, Zhou Gang, Xiong Xiaobing. Detecting Overlapping Community Structure with Neighbor Voting[J]. Journal of Chinese Computer Systems, 2014,35(10):2272-2277.)
[23]
Nepusz T, Petróczi A, Négyessy L, et al. Fuzzy Communities and the Concept of Bridgeness in Complex Networks[J]. Physical Review E Statal Nonlinear & Soft Matter Physics, 2008,77(1):016107.
[24]
Nicosia V, Mangioni G, Carchiolo V, et al. Extending the Definition of Modularity to Directed Graphs with Overlapping Communities[J]. Journal of Statal Mechanics Theory & Experiment, 2009(3):3166-3168.
( Han Zhongming, Liu Wen, Li Mengqi, et al. Community Detection Algorithm Based on Node Embedding Vector Representation[J]. Journal of Software, 2019,30(4):1045-1061.)
[27]
Rhouma D, Romdhane L B. An Efficient Algorithm for Community Mining with Overlap in Social Networks[J]. Expert Systems with Applications, 2014,41(9):4309-4321.
doi: 10.1016/j.eswa.2014.01.002
( Zhao Quanhua, Li Xiaoli, Zhao Xuemei, et al. Fuzzy Clustering Algorithm Based on Spatially Constrained Student’s-T Mixture Model for Image Segmentation[J]. Control and Decision, 2016,31(11):2065-2070.)
[29]
Rasmussen C E. The Infinite Gaussian Mixture Model[C]// Proceedings of the Advances in Neural Information Processing Systems 12. 2000: 554-560.
[30]
Clauset A, Newman M E, Moore C. Finding Community Structure in Very Large Networks[J]. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics, 2004,70(6):066111.
doi: 10.1103/PhysRevE.70.066111
[31]
Lancichinetti A, Fortunato S. Benchmarks for Testing Community Detection Algorithms on Directed and Weighted Graphs with Overlapping Communities[J]. Physical Review. E, Statistical,Nonlinear and Soft Matter Physics, 2009,80(2):016118.
doi: 10.1103/PhysRevE.80.016118
[32]
van der Maaten L, Hinton G. Visualizing Data Using t-SNE[J]. Journal of Machine Learning Research, 2008,9(86):2579-2605.
[33]
Conrad L, Fergal R, Aaron M, et al. Detecting Highly Overlapping Community Structure by Greedy Clique Expansion[OL]. arXiv Preprint, arXiv: 1002. 1827.
[34]
Wu Z H, Lin Y F, Gregory S, et al. Balanced Multi-Label Propagation for Overlapping Community Detection in Social Networks[J]. Journal of Computer Science and Technology, 2012,27(3):468-479.
doi: 10.1007/s11390-012-1236-x
[35]
Palla G, Derényi I, Farkas I, et al. Uncovering the Overlapping Community Structure of Complex Networks in Nature and Society[J]. Nature, 2005,435(7043):814.
doi: 10.1038/nature03607
