IDEAS home Printed from https://ideas.repec.org/a/hin/complx/3475458.html
   My bibliography  Save this article

A Semantic Community Detection Algorithm Based on Quantizing Progress

Author

Listed:
  • Xu Han
  • Deyun Chen
  • Hailu Yang

Abstract

The semantic social network is a kind of network that contains enormous nodes and complex semantic information, and the traditional community detection algorithms could not give the ideal cogent communities instead. To solve the issue of detecting semantic social network, we present a clustering community detection algorithm based on the PSO-LDA model. As the semantic model is LDA model, we use the Gibbs sampling method that can make quantitative parameters map from semantic information to semantic space. Then, we present a PSO strategy with the semantic relation to solve the overlapping community detection. Finally, we establish semantic modularity (SimQ) for evaluating the detected semantic communities. The validity and feasibility of the PSO-LDA model and the semantic modularity are verified by experimental analysis.

Suggested Citation

  • Xu Han & Deyun Chen & Hailu Yang, 2019. "A Semantic Community Detection Algorithm Based on Quantizing Progress," Complexity, Hindawi, vol. 2019, pages 1-13, January.
    • Handle: RePEc:hin:complx:3475458
    DOI: 10.1155/2019/3475458
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2019/3475458.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2019/3475458.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2019/3475458?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
    ---><---

    References listed on IDEAS

    as
    1. Shen, Huawei & Cheng, Xueqi & Cai, Kai & Hu, Mao-Bin, 2009. "Detect overlapping and hierarchical community structure in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1706-1712.
    2. Yair Neuman & Yiftach Neuman & Yochai Cohen, 2017. "A Novel Procedure for Measuring Semantic Synergy," Complexity, Hindawi, vol. 2017, pages 1-8, January.
    3. Ulzii-Utas Narantsatsralt & Sanggil Kang, 2017. "Social Network Community Detection Using Agglomerative Spectral Clustering," Complexity, Hindawi, vol. 2017, pages 1-10, November.
    Full references (including those not matched with items on IDEAS)

    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. Cui, Yaozu & Wang, Xingyuan & Eustace, Justine, 2014. "Detecting community structure via the maximal sub-graphs and belonging degrees in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 198-207.
    2. Wu, Zhihao & Lin, Youfang & Wan, Huaiyu & Tian, Shengfeng & Hu, Keyun, 2012. "Efficient overlapping community detection in huge real-world networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(7), pages 2475-2490.
    3. Mucunska Palevska, Valentina & Novkovska, Blagica, 2021. "Increasing Use Of Digital Technologies In Function Of Economic Growth In European Countries," UTMS Journal of Economics, University of Tourism and Management, Skopje, Macedonia, vol. 12(1), pages 84-94.
    4. Wu, Jianshe & Wang, Xiaohua & Jiao, Licheng, 2012. "Synchronization on overlapping community network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(3), pages 508-514.
    5. Shang, Ronghua & Luo, Shuang & Zhang, Weitong & Stolkin, Rustam & Jiao, Licheng, 2016. "A multiobjective evolutionary algorithm to find community structures based on affinity propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 203-227.
    6. 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.
    7. Fu, Xianghua & Liu, Liandong & Wang, Chao, 2013. "Detection of community overlap according to belief propagation and conflict," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(4), pages 941-952.
    8. Hao Xu & Yuan Ran & Junqian Xing & Li Tao, 2023. "An Influence-Based Label Propagation Algorithm for Overlapping Community Detection," Mathematics, MDPI, vol. 11(9), pages 1-17, May.
    9. Wu, Tao & Guo, Yuxiao & Chen, Leiting & Liu, Yanbing, 2016. "Integrated structure investigation in complex networks by label propagation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 448(C), pages 68-80.
    10. Hailu Yang & Deyun Chen & Guanglu Sun & Xiaoyu Ding & Yu Xin, 2019. "CC 2 : Defending Hybrid Worm on Mobile Networks with Two-Dimensional Circulation Control," Complexity, Hindawi, vol. 2019, pages 1-19, December.
    11. Franck Marle & Hadi Jaber & Catherine Pointurier, 2019. "Organizing Project Actors for Collective Decision-Making about Interdependent Risks," Complexity, Hindawi, vol. 2019, pages 1-18, March.
    12. Wu, Jianshe & Hou, Yunting & Jiao, Yang & Li, Yong & Li, Xiaoxiao & Jiao, Licheng, 2015. "Density shrinking algorithm for community detection with path based similarity," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 433(C), pages 218-228.
    13. 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.
    14. Nedioui, Med Abdelhamid & Moussaoui, Abdelouahab & Saoud, Bilal & Babahenini, Mohamed Chaouki, 2020. "Detecting communities in social networks based on cliques," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 551(C).
    15. Sun, Xiao-Qian & Shen, Hua-Wei & Cheng, Xue-Qi & Zhang, Yuqing, 2017. "Detecting anomalous traders using multi-slice network analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 1-9.
    16. Yang, Jin-Xuan & Zhang, Xiao-Dong, 2017. "Finding overlapping communities using seed set," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 467(C), pages 96-106.
    17. Mu, Caihong & Liu, Yong & Liu, Yi & Wu, Jianshe & Jiao, Licheng, 2014. "Two-stage algorithm using influence coefficient for detecting the hierarchical, non-overlapping and overlapping community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 47-61.
    18. Feng, Liang & Zhao, Qianchuan & Zhou, Cangqi, 2021. "Incorporating affiliation preference into overlapping community detection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    19. Eustace, Justine & Wang, Xingyuan & Cui, Yaozu, 2015. "Community detection using local neighborhood in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 665-677.
    20. Manini Madireddy & Ramasubramanian Sundararajan & Goda Doreswamy & Meisam Hejazi Nia & Amod Mital, 2017. "Constructing bundled offers for airline customers," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 16(6), pages 532-552, December.

    More about this item

    Statistics

    Access and download statistics

    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:hin:complx:3475458. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    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.