Computer Science

Computer Science ›› 2023, Vol. 50 ›› Issue (6A): 220200015-6.doi: 10.11896/jsjkx.220200015

• Big Data & Data Science • Previous Articles     Next Articles

Local Community Detection Algorithm for Attribute Networks Based on Multi-objective Particle Swarm Optimization

ZHOU Zhiqiang, ZHU Yan   

  1. School of Computing and Artificial Intelligence,Southwest Jiaotong University,Chengdu 611756,China
  • Online:2023-06-10 Published:2023-06-12
  • About author:ZHOU Zhiqiang,born in 1997,master candidate.His main research interests includes social network data mining and community detection. ZHU Yan,born in 1965,Ph.D,professor,is a member of China Computer Federation.Her main research interests includes data mining and social network analysis and mining.
  • Supported by:
    This work was supported by Sichuan Provincial Science and Technology Plan Project(2019YFSY0032).

PDF (PC)

223

Abstract: Community structure is an important feature in complex networks,and the goal of local community detection is to query a community subgraph containing a set of seed nodes.Traditional local community detection algorithms usually use the topology of the network for community query,ignoring the rich node attribute information in the network.A local community detection algorithm based on multi-objective particle swarm optimization is proposed for realistic and widespread attribute networks.Firstly,attribute relationship edges are constructed based on the attribute similarity between nodes and their multi-order neighbours,and topological relationship edges are obtained by weighting the network structure based on the motif information,followed by sampling the two relationship edges around the core nodes using a random walk algorithm to obtain alternative node sets.Based on this,the alternative node sets are iteratively filtered by a multi-objective particle swarm optimization algorithm to obtain a topologically tight and attribute-homogeneous community structure.Experimental results on real datasets show that the proposed method improves the performance of local community detection.

Key words: Local community detection, Attribute networks, Motif, Multi-objective particle swarm optimization, Information entropy

CLC Number: 

  • TP391
[1]GASPARETTI F,SANSONETTI G.Community detection insocial recommender systems:a survey[J].Applied Intelligence,2021,51(6):3975-3995.
[2]DILMAGHANI S E,MATTHIAS R.Community Detection in Complex Networks:A Survey on Local Approaches[J].ACIIDS,2021,13:757-767.
[3]CHUNAEV P.Community detection in node-attributed socialnetworks:A survey[J].Computer Science Review,2020,37:100286.
[4]LUO W J,LU N,NI L,et al.Local community detection by the nearest nodes with greater centrality[J].Inormation Sciences,2020,517:377-392.
[5]TONG H,FALOUTSOS C,PAN J Y.Fast random walk with restart and its applications[C]//Proc.6th Int.Conf.Data Mining,Hong Kong,China:IEEE,2006:613-622.
[6]BIAN Y C,NI J C,CHENG W,et al.Many Heads are Better than One:Local Community Detection by the Multi-walker Chain[C]//Proc.Int.Conf.Data Mining,New Orleans,USA:IEEE,2017:21-30.
[7]YU S,FENG Y F,ZHANG D,et al.Motif discovery in net-works:A survey[J].Computer Science Review,2020,37:100267.
[8]YIN H,BENSON A R,LESKOVEC J,et al.Local higher-order graphclustering[C]//Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mi-ning.2017:555-564.
[9]LI P Z,HUANG L,WANG C D,et al.Edmot:An edge enhancement approach for motif-aware community detection[C]//Proceedings ofthe 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining.2019:479-487.
[10]ZHAO H,ZHOU Y,SONG Y,et al.Motif enhanced recommendation over heterogeneous information network[C]//Procee-dings of the 28th ACM International Conference on Information and Knowledge Management.2019:2189-2192.
[11]ALINEZHAD E,TEIMOURPOUR B,SEPEHRI M M,et al.Community detection in attributed networks considering both structural and attribute similarities:two mathematical programming approaches[J].Neural Computing & Applications,2020,32(8):3203-3220.
[12]XU X,XIAO Y,LONG H,et al.Attributed Network Embedding Based on Matrix Factorization and Community Detection[J].Computer Science,2021,48(12):204-211.
[13]ZHANG Q,LIU M.Multi-objective Five-elements Cycle Optimization Algorithm for Complex Network Community Discovery[J].Computer Science,2020,47(8):284-290.
[14]RAHIMI S,ABDOLLAHPOURI A,MORADI P.A multi-objective particle swarm optimization algorithm for community detection in complex networks[J].Swarm and Evolutionary Computation,2018,39:297-309.
[1] XIA Yuan, ZHAO Yun-long, FAN Qi-lin. Data Stream Ensemble Classification Algorithm Based on Information Entropy Updating Weight [J]. Computer Science, 2022, 49(3): 92-98.
[2] ZHOU Gang, GUO Fu-liang. Research on Ensemble Learning Method Based on Feature Selection for High-dimensional Data [J]. Computer Science, 2021, 48(6A): 250-254.
[3] ZHAO Qin-yan, LI Zong-min, LIU Yu-jie, LI Hua. Cascaded Siamese Network Visual Tracking Based on Information Entropy [J]. Computer Science, 2020, 47(9): 157-162.
[4] LIU Zi-qi, GUO Bing-hui, CHENG Zhen, YANG Xiao-bo and YIN Zi-qiao. Science and Technology Strategy Evaluation Based on Entropy Fuzzy AHP [J]. Computer Science, 2020, 47(6A): 1-5.
[5] WANG Ya-ge, KANG Xiao-dong, GUO Jun, HONG Rui, LI Bo, ZHANG Xiu-fang. Image Compression Method Combining Canny Edge Detection and SPIHT [J]. Computer Science, 2019, 46(6A): 222-225.
[6] ZHANG Fang, ZHAO Shu-liang, WU Yong-liang. Data Scaling Method for Multi-scale Data Mining [J]. Computer Science, 2019, 46(4): 57-65.
[7] ZHU Pei-pei, LONG Min. Recommendation Methods Considering User Indirect Trust and Gaussian Filling [J]. Computer Science, 2019, 46(11A): 178-184.
[8] WANG Yi-bo, PENG Guang-ju, HE Yuan-duo, WANG Ya-sha, ZHAO Jun-feng, WANG Jiang-tao. Time Series Motif Discovery Algorithm of Variable Length Based on Domain Preference [J]. Computer Science, 2019, 46(11): 251-259.
[9] ZHENG Shu-fu,YU Gao-feng. Attribute Transfer and Knowledge Discovery Based on Formal Context [J]. Computer Science, 2018, 45(6A): 117-119.
[10] WANG Feng, LIU Ji-chao, WEI Wei. Semi-supervised Feature Selection Algorithm Based on Information Entropy [J]. Computer Science, 2018, 45(11A): 427-430.
[11] ZOU Na, TIAN Jin-wen. Research on Multi Feature Fusion Infrared Ship Wake Detection [J]. Computer Science, 2018, 45(11A): 172-175.
[12] YUAN Xiao-yan, WANG An-zhi, PAN Gang and WANG Ming-hui. Visual Attention Modeling Based on Multi-scale Fusion of Amplitude Spectrum and Phase Spectrum [J]. Computer Science, 2017, 44(7): 293-298.
[13] YANG Ying-hui, LI Jian-hua, NAN Ming-li, CUI Qiong and WANG Hong. Networked Operational Information Flowing Dynamic Hypergraph Model Based on Motif [J]. Computer Science, 2016, 43(8): 30-35.
[14] ZHANG Heng-wei, HAN Ji-hong, WEI Bo and WANG Jin-dong. Research on Cloud Resource Scheduling Method Based on Map-Reduce [J]. Computer Science, 2015, 42(8): 118-123.
[15] WANG Feng WEI Wei. Group Feature Selection Algorithm for Data Sets with Missing Data [J]. Computer Science, 2015, 42(7): 285-290.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.