Journal of Shandong University(Engineering Science) ›› 2025, Vol. 55 ›› Issue (1): 41-50.doi: 10.6040/j.issn.1672-3961.0.2024.191

• Machine Learning & Data Mining • Previous Articles     Next Articles

Community detection algorithm based on dual-view network embedded clustering integration

WANG Yingnan1, ZHENG Wenping2,3*, YANG Gui2   

  1. 1. Fenyang College of Shanxi Medical University, Fenyang 032200, Shanxi, China;
    2. School of Computer and Information Technology, Shanxi University, Taiyuan 030006, Shanxi, China;
    3. Key Laboratory of Computation Intelligence and Chinese Information Processing of Ministry of Education, Shanxi University, Taiyuan 030006, Shanxi, China
  • Published:2025-02-20

PDF (PC)

109

CLC Number: 

  • TP391
[1] BLONDEL V D, GUILLAUME J, LAMBIOTTE R. Fast Unfolding of Communities in Large Networks[J]. Journal of Statistical Mechanics: Theory and Experiment, 2008, 2008(10):10008.
[2] NEWMAN M E J. Fast algorithm for detecting community structure in networks[J]. Physical Review E, 2004, 69(6):66133.
[3] CLAUSET A, NEWMAN M E J, MOORE C. Finding community structure in very large networks[J]. Physical Review E, 2004, 70(2): 66111.
[4] RAGHAVAN U N, ALBERT R, KUMARA S. Near linear time algorithm to detect community structures in large-scale networks[J]. Physical Review E, 2007, 76(3): 36106.
[5] BARBER M J, CLARK J W. Detecting network communities by propagating labels under constraints[J].Physical Review E, 2009, 80(2): 26129.
[6] BELKIN M, NIYOGI P. Laplacian eigenmaps and spectral techniques for embedding and clustering[J]. Advances in Neural Information Processing Systems, 2001, 14(6): 585-591.
[7] TENENBAUM J B, DE SILVA V, LANGGORD J C. A global geometric framework for nonlinear dimensionality reduction[J]. Science, 2000, 290(5500): 2319-2323.
[8] ROWEIS S T, SAUL L K. Nonlinear dimensionality reduction by locally linear embedding[J]. Science, 2000(290): 2323-2326.
[9] PEROZZI B, AL-RFOU R,SKIENA S. DeepWalk: online learning of social representations[C] // Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, USA: ACM, 2014: 701-710.
[10] GROVER A, LESKOVEC J. Node2vec: scalable feature learning for networks[C] // Proceedings of the 22th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, USA: ACM, 2016: 855-864.
[11] WANG D X, CUI P, ZHU WW. Structural deep network embedding[C] // Proceedings of 22th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, USA: ACM, 2016: 1225-1234.
[12] CAO SS, LU W, XU Q K. Deep neural networks for learning graph representations[C] // Proceedings of the 30th AAAI Conference on Artificial Intelligence. Palo Alto, USA: AAAI Press, 2016: 1145-1152.
[13] WANG Xiao, CUI Peng, WANG Jing, et al. Community preserving network embedding[C] // Proceedings of the 32th AAAI Conference on Artificial Intelligence. Palo Alto, USA: AAAI press, 2017: 203-209.
[14] YANG C, LIU Z Y, ZHAO D L. Network representation learning with rich text information[C] // Proceedings of the 24th International Joint Conference on Artificial Intelligence. Palo Alto, USA: AAAI Press, 2015: 2111-2117.
[15] HUANG X, LI J D, HU X. Accelerated attributed network embedding[C] // Proceedings of the 2017 SIAM International Conference on Data Mining. Philadelphia, USA: SIAM, 2017: 633-641.
[16] KIPF T N, WELLING M. Semi-supervised classification with graph convolutional networks[C] // International Conference on Learning Representations. Toulon, France: ICLR, 2016: 718-725.
[17] VELICKOVIC P, CUCURULL G, GASANOVA A, et al. Graph attention networks[C] //Proceedings of the Int Conf on Learning Representations. Vancouver, Canada: ICLR, 2018: 485-497.
[18] KIPF T N, WELLING M. Variational graph auto-encoders[C] // Proceedings of the NIPS Workshopon Bayesian Deep Learning. Barcelona, Spain: NIPS, 2016: 1611-1616.
[19] SALEHI A, DAVULCU H. Graph attention auto-encoders [C] // Proceedings of the 32nd IEEE International Conference on Tools with Artificial Intelligence. Piscataway, USA: IEEE, 2020: 989-996.
[20] XIE J Y, GIRSHICK R, FARHADI A. Unsupervised deep embedding for clustering analysis[C] // Proceedings of the 33rd International Conference on Machine Learning. New York, USA: ACM, 2016: 478-487.
[21] WANG C, PAN S R, HU R Q, et al. Attributed graph clustering: a deep attentional embedding approach[C] // Proceedings of 28th International Joint Conference on Artificial Intelligence. San Francisco, USA: Morgan Kaufmann, 2019: 3670-3676.
[22] BO D Y, WANG X, SHI C, et al. Structural deep clustering network[C] // Proceedings of the 29th International World Wide Web Conference. New York, USA: ACM, 2020: 1400-1410.
[23] 郑文萍,王英楠,杨贵.基于双监督网络嵌入的社区发现算法[J]. 模式识别与人工智能, 2022, 35(3): 283-290. ZHENG Wenping, WANG Yingnan, YANG Gui. Dual supervised network embedding based community detection algorithm[J]. Pattern Recognition and Artificial Intelligence, 2022, 35(3): 283-290.
[24] PAN Shirui, HU Ruiqi, JIANG Jing, et al. Adversarially regularized graph auto-encoder for graph embedding[C] // Proceedings of the 27th International Joint Conference on Artificial Intelligence. Melbourne, Australia: IJCAI, 2018: 2609-2615.
[1] DENG Bin, ZHANG Zongbao, ZHAO Wenmeng, LUO Xinhang, WU Qiuwei. Cloud-edge collaborative and graph neural network based load forecasting method for electric vehicle charging stations [J]. Journal of Shandong University(Engineering Science), 2025, 55(5): 62-69.
[2] LI Erchao, ZHANG Zhizhao. Online dynamic demand vehicle routing planning [J]. Journal of Shandong University(Engineering Science), 2024, 54(5): 62-73.
[3] YANG Jucheng, WEI Feng, LIN Liang, JIA Qingxiang, LIU Jianzheng. A research survey of driver drowsiness driving detection [J]. Journal of Shandong University(Engineering Science), 2024, 54(2): 1-12.
[4] XIAO Wei, ZHENG Gengsheng, CHEN Yujia. Named entity recognition method combined with self-training model [J]. Journal of Shandong University(Engineering Science), 2024, 54(2): 96-102.
[5] Gang HU, Lemeng WANG, Zhiyu LU, Qin WANG, Xiang XU. Importance identification method based on multi-order neighborhood hierarchical association contribution of nodes [J]. Journal of Shandong University(Engineering Science), 2024, 54(1): 1-10.
[6] Jiachun LI,Bowen LI,Jianbo CHANG. An efficient and lightweight RGB frame-level face anti-spoofing model [J]. Journal of Shandong University(Engineering Science), 2023, 53(6): 1-7.
[7] Yujiang FAN,Huanhuan HUANG,Jiaxiong DING,Kai LIAO,Binshan YU. Resilience evaluation system of the old community based on cloud model [J]. Journal of Shandong University(Engineering Science), 2023, 53(5): 1-9, 19.
[8] Ying LI,Jiankun WANG. The classification of mild cognitive impairment based on supervised graph regularization and information fusion [J]. Journal of Shandong University(Engineering Science), 2023, 53(4): 65-73.
[9] WU Yanli, LIU Shuwei, HE Dongxiao, WANG Xiaobao, JIN Di. Poisson-gamma topic model of describing multiple underlying relationships [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 51-60.
[10] YU Mingjun, DIAO Hongjun, LING Xinghong. Online multi-object tracking method based on trajectory mask [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 61-69.
[11] LIU Xing, YANG Lu, HAO Fanchang. Finger vein image retrieval based on multi-feature fusion [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 118-126.
[12] LIU Fangxu, WANG Jian, WEI Benzheng. Auxiliary diagnosis algorithm for pediatric pneumonia based on multi-spatial attention [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 135-142.
[13] YU Yixuan, YANG Geng, GENG Hua. Multimodal hierarchical keyframe extraction method for continuous combined motion [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 42-50.
[14] HUANG Huajuan, CHENG Qian, WEI Xiuxi, YU Chuchu. Adaptive crow search algorithm with Jaya algorithm and Gaussian mutation [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 11-22.
[15] ZHANG Hao, LI Ziling, LIU Tong, ZHANG Dawei, TAO Jianhua. A technology prediction model based on fuzzy Bayesian networks with sociological factors [J]. Journal of Shandong University(Engineering Science), 2023, 53(2): 23-33.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] SHI Lai-shun,WAN Zhong-yi . Synthesis and performance evaluation of a novel betaine-type asphalt emulsifier[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2008, 38(4): 112 -115 .
[2] JI Tao,GAO Xu/sup>,SUN Tong-jing,XUE Yong-duan/sup>,XU Bing-yin/sup> . Characteristic analysis of fault generated traveling waves in 10 Kv automatic blocking and continuous power transmission lines[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2006, 36(2): 111 -116 .
[3] SUN Cong-zheng,GUAN Cong-sheng,QIN Jing-yu,CHENG Chuan . The structure and performances of the electroless Ni-P alloy coating on aluminum alloy[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2007, 37(5): 108 -112 .
[4] XIA Bin,ZHANG Lian-jun . Energy comparison-based TOA estimation algorithm for the DS-CDMA UWB system[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2007, 37(1): 70 -73 .
[5] HU Tian-liang,LI Peng,ZHANG Cheng-rui,ZUO Yi . Design of a QEP decode counter based on VHDL[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2008, 38(3): 10 -13 .
[6] . [J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(2): 104 -107 .
[7] WANG Ru-gui,CAI Gan-wei . Sub-harmonic resonance analysis of 2-DOF controllable plane linkage mechanism electromechanical coupling system[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2008, 38(3): 58 -63 .
[8] SHI Wen-Hua, LIU Wei-Dong, SUN Yong-Fu. Research of 1／3 dam breach simulation and personnel evacuation scenario based on digital elevation model DEM in a quake lake[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2009, 39(5): 144 -148 .
[9] MENG Jian, LI Yibin, LI Bin. Bound gait controlling method of quadruped robot[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2015, 45(3): 28 -34 .
[10] XU Yan-sheng,LIU Xing-fang . Application of the fuzzy clustering iterative model to the evalution of water resource carrying capacity[J]. JOURNAL OF SHANDONG UNIVERSITY (ENGINEERING SCIENCE), 2007, 37(3): 100 -104 .
Copyright 2018 © Editorial office of Journal of Shandong University (Engineering Science)
Supported by Beijing Magtech Co.Ltd