IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v464y2016icp221-230.html
   My bibliography  Save this article

Community detection in complex networks using density-based clustering algorithm and manifold learning

Author

Listed:
  • You, Tao
  • Cheng, Hui-Min
  • Ning, Yi-Zi
  • Shia, Ben-Chang
  • Zhang, Zhong-Yuan

Abstract

Like clustering analysis, community detection aims at assigning nodes in a network into different communities. Fdp is a recently proposed density-based clustering algorithm which does not need the number of clusters as prior input and the result is insensitive to its parameter. However, Fdp cannot be directly applied to community detection due to its inability to recognize the community centers in the network. To solve the problem, a new community detection method (named IsoFdp) is proposed in this paper. First, we use IsoMap technique to map the network data into a low dimensional manifold which can reveal diverse pair-wised similarity. Then Fdp is applied to detect the communities in the network. An improved partition density function is proposed to select the proper number of communities automatically. We test our method on both synthetic and real-world networks, and the results demonstrate the effectiveness of our algorithm over the state-of-the-art methods.

Suggested Citation

  • You, Tao & Cheng, Hui-Min & Ning, Yi-Zi & Shia, Ben-Chang & Zhang, Zhong-Yuan, 2016. "Community detection in complex networks using density-based clustering algorithm and manifold learning," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 464(C), pages 221-230.
  • Handle: RePEc:eee:phsmap:v:464:y:2016:i:c:p:221-230
    DOI: 10.1016/j.physa.2016.07.025
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437116304563
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

    File URL: https://libkey.io/10.1016/j.physa.2016.07.025?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Wang, Wenjun & Liu, Dong & Liu, Xiao & Pan, Lin, 2013. "Fuzzy overlapping community detection based on local random walk and multidimensional scaling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6578-6586.
    2. Yong-Yeol Ahn & James P. Bagrow & Sune Lehmann, 2010. "Link communities reveal multiscale complexity in networks," Nature, Nature, vol. 466(7307), pages 761-764, August.
    3. Pablo M. Gleiser & Leon Danon, 2003. "Community Structure In Jazz," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 6(04), pages 565-573.
    4. Jiang, Yawen & Jia, Caiyan & Yu, Jian, 2013. "An efficient community detection method based on rank centrality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(9), pages 2182-2194.
    5. Zhong-Yuan Zhang & Yong-Yeol Ahn, 2015. "Community detection in bipartite networks using weighted symmetric binary matrix factorization," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 26(09), pages 1-14.
    6. Xiang-Sun Zhang & Zhenping Li & Rui-Sheng Wang & Yong Wang, 2012. "A combinatorial model and algorithm for globally searching community structure in complex networks," Journal of Combinatorial Optimization, Springer, vol. 23(4), pages 425-442, May.
    7. Ma, Xiaoke & Gao, Lin & Yong, Xuerong & Fu, Lidong, 2010. "Semi-supervised clustering algorithm for community structure detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(1), pages 187-197.
    8. Lü, Linyuan & Zhou, Tao, 2011. "Link prediction in complex networks: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(6), pages 1150-1170.
    9. Gong, Maoguo & Liu, Jie & Ma, Lijia & Cai, Qing & Jiao, Licheng, 2014. "Novel heuristic density-based method for community detection in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 71-84.
    10. Jin, Hong & Wang, Shuliang & Li, Chenyang, 2013. "Community detection in complex networks by density-based clustering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(19), pages 4606-4618.
    11. Zhang, Shihua & Wang, Rui-Sheng & Zhang, Xiang-Sun, 2007. "Identification of overlapping community structure in complex networks using fuzzy c-means clustering," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 374(1), pages 483-490.
    12. Medus, A. & Acuña, G. & Dorso, C.O., 2005. "Detection of community structures in networks via global optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 358(2), pages 593-604.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ke Hu & Ju Xiang & Yun-Xia Yu & Liang Tang & Qin Xiang & Jian-Ming Li & Yong-Hong Tang & Yong-Jun Chen & Yan Zhang, 2020. "Significance-based multi-scale method for network community detection and its application in disease-gene prediction," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-24, March.
    2. Zhang, Weitong & Zhang, Rui & Shang, Ronghua & Li, Juanfei & Jiao, Licheng, 2019. "Application of natural computation inspired method in community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 515(C), pages 130-150.
    3. Li, Yafang & Jia, Caiyan & Li, Jianqiang & Wang, Xiaoyang & Yu, Jian, 2018. "Enhanced semi-supervised community detection with active node and link selection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 219-232.
    4. Jianjun Cheng & Xing Su & Haijuan Yang & Longjie Li & Jingming Zhang & Shiyan Zhao & Xiaoyun Chen, 2019. "Neighbor Similarity Based Agglomerative Method for Community Detection in Networks," Complexity, Hindawi, vol. 2019, pages 1-16, May.
    5. Ding, Jiajun & He, Xiongxiong & Yuan, Junqing & Chen, Yan & Jiang, Bo, 2018. "Community detection by propagating the label of center," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 675-686.
    6. Sun, Jun-yan & Tang, Jian-ming & Fu, Wei-ping & Wu, Bing-ying, 2017. "Hybrid modeling and empirical analysis of automobile supply chain network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 377-389.
    7. Huang, Yan & Wan, Jiansong & Huang, Xin, 2019. "Quantitative analysis of financial system fragility based on manifold curvature," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 1276-1285.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Li, Yafang & Jia, Caiyan & Yu, Jian, 2015. "A parameter-free community detection method based on centrality and dispersion of nodes in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 321-334.
    2. Li, Yafang & Jia, Caiyan & Li, Jianqiang & Wang, Xiaoyang & Yu, Jian, 2018. "Enhanced semi-supervised community detection with active node and link selection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 219-232.
    3. Zhou, Xu & Liu, Yanheng & Zhang, Jindong & Liu, Tuming & Zhang, Di, 2015. "An ant colony based algorithm for overlapping community detection in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 427(C), pages 289-301.
    4. Yazdanparast, Sakineh & Havens, Timothy C., 2017. "Modularity maximization using completely positive programming," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 20-32.
    5. Gholami, Maryam & Sheikhahmadi, Amir & Khamforoosh, Keyhan & Jalili, Mahdi, 2022. "Overlapping community detection in networks based on Neutrosophic theory," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 598(C).
    6. Zhou, Wen & Jia, Yifan, 2017. "Predicting links based on knowledge dissemination in complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 561-568.
    7. Zhou, Xu & Liu, Yanheng & Wang, Jian & Li, Chun, 2017. "A density based link clustering algorithm for overlapping community detection in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 65-78.
    8. Xiaofeng Wang & Gongshen Liu & Jianhua Li & Jan P Nees, 2017. "Locating Structural Centers: A Density-Based Clustering Method for Community Detection," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-23, January.
    9. Wang, Tao & Yin, Liyan & Wang, Xiaoxia, 2018. "A community detection method based on local similarity and degree clustering information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 490(C), pages 1344-1354.
    10. Hu, Fang & Liu, Yuhua, 2016. "A new algorithm CNM-Centrality of detecting communities based on node centrality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 446(C), pages 138-151.
    11. Jing Wang & Jing Wang & Jingfeng Guo & Liya Wang & Chunying Zhang & Bin Liu, 2023. "Research Progress of Complex Network Modeling Methods Based on Uncertainty Theory," Mathematics, MDPI, vol. 11(5), pages 1-27, March.
    12. Liu, X. & Murata, T., 2010. "Advanced modularity-specialized label propagation algorithm for detecting communities in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 389(7), pages 1493-1500.
    13. Badie, Reza & Aleahmad, Abolfazl & Asadpour, Masoud & Rahgozar, Maseud, 2013. "An efficient agent-based algorithm for overlapping community detection using nodes’ closeness," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5231-5247.
    14. Xu, Shuang & Wang, Pei, 2017. "Identifying important nodes by adaptive LeaderRank," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 469(C), pages 654-664.
    15. Wang, Wenjun & Liu, Dong & Liu, Xiao & Pan, Lin, 2013. "Fuzzy overlapping community detection based on local random walk and multidimensional scaling," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(24), pages 6578-6586.
    16. Zhou, Kuang & Martin, Arnaud & Pan, Quan, 2015. "A similarity-based community detection method with multiple prototype representation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 438(C), pages 519-531.
    17. Gao, Cai & Wei, Daijun & Hu, Yong & Mahadevan, Sankaran & Deng, Yong, 2013. "A modified evidential methodology of identifying influential nodes in weighted networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5490-5500.
    18. Abdolhosseini-Qomi, Amir Mahdi & Yazdani, Naser & Asadpour, Masoud, 2020. "Overlapping communities and the prediction of missing links in multiplex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 554(C).
    19. Eustace, Justine & Wang, Xingyuan & Cui, Yaozu, 2015. "Overlapping community detection using neighborhood ratio matrix," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 421(C), pages 510-521.
    20. Zhang, Zhong-Yuan & Gai, Yujie & Wang, Yu-Fei & Cheng, Hui-Min & Liu, Xin, 2018. "On equivalence of likelihood maximization of stochastic block model and constrained nonnegative matrix factorization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 687-697.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:464:y:2016:i:c:p:221-230. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.