IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v566y2021ics0378437120309596.html
   My bibliography  Save this article

Discovering latent structures with integrated propagation algorithms in geographical information networks

Author

Listed:
  • Qu, Yingfei
  • Tang, Lianggui
  • Yan, Huyong

Abstract

The real-world exists various kinds of complex network systems, including geographical information systems (GIS) as the important components. However, it is hard to understand the functions scientifically because that the structures are latent for our eyes in these systems. In this paper, a specific model is proposed to deal with the expression of geographical information networks. And by integrating the belief propagation algorithm and label propagation algorithm, our algorithm is able to discover the latent structures and achieve some understandings of the networks without knowing the number of communities. We test the algorithm on the benchmark networks as well as the real-world subway-road networks. The results show the availability for the applications of our algorithm to the geographical information networks.

Suggested Citation

  • Qu, Yingfei & Tang, Lianggui & Yan, Huyong, 2021. "Discovering latent structures with integrated propagation algorithms in geographical information networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
  • Handle: RePEc:eee:phsmap:v:566:y:2021:i:c:s0378437120309596
    DOI: 10.1016/j.physa.2020.125661
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437120309596
    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.2020.125661?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. Lu, Feng & Liu, Kang & Duan, Yingying & Cheng, Shifen & Du, Fei, 2018. "Modeling the heterogeneous traffic correlations in urban road systems using traffic-enhanced community detection approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 501(C), pages 227-237.
    2. Andrea Lancichinetti & Filippo Radicchi & José J Ramasco & Santo Fortunato, 2011. "Finding Statistically Significant Communities in Networks," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-18, April.
    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. Wu, Jianshe & Zhang, Long & Li, Yong & Jiao, Yang, 2016. "Partition signed social networks via clustering dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 443(C), pages 568-582.
    2. Gregory, Steve, 2012. "Ordered community structure in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(8), pages 2752-2763.
    3. 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.
    4. Greg Morrison & L Mahadevan, 2012. "Discovering Communities through Friendship," PLOS ONE, Public Library of Science, vol. 7(7), pages 1-9, July.
    5. 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.
    6. Franke, R., 2016. "CHIMERA: Top-down model for hierarchical, overlapping and directed cluster structures in directed and weighted complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 384-408.
    7. Chagas, Guilherme Oliveira & Lorena, Luiz Antonio Nogueira & dos Santos, Rafael Duarte Coelho, 2022. "A hybrid heuristic for overlapping community detection through the conductance minimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 592(C).
    8. Dugué, Nicolas & Perez, Anthony, 2022. "Direction matters in complex networks: A theoretical and applied study for greedy modularity optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 603(C).
    9. 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.
    10. Klapka, Pavel & Kraft, Stanislav & Halás, Marián, 2020. "Network based definition of functional regions: A graph theory approach for spatial distribution of traffic flows," Journal of Transport Geography, Elsevier, vol. 88(C).
    11. Wang, Yuyao & Bu, Zhan & Yang, Huan & Li, Hui-Jia & Cao, Jie, 2021. "An effective and scalable overlapping community detection approach: Integrating social identity model and game theory," Applied Mathematics and Computation, Elsevier, vol. 390(C).
    12. 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.
    13. Dafne E. van Kuppevelt & Rena Bakhshi & Eelke M. Heemskerk & Frank W. Takes, 2022. "Community membership consistency applied to corporate board interlock networks," Journal of Computational Social Science, Springer, vol. 5(1), pages 841-860, May.
    14. Jiang, Zhongzhou & Liu, Jing & Wang, Shuai, 2016. "Traveling salesman problems with PageRank Distance on complex networks reveal community structure," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 463(C), pages 293-302.
    15. Kyle F Davis & Paolo D'Odorico & Francesco Laio & Luca Ridolfi, 2013. "Global Spatio-Temporal Patterns in Human Migration: A Complex Network Perspective," PLOS ONE, Public Library of Science, vol. 8(1), pages 1-8, January.
    16. Lovro Šubelj & Nees Jan van Eck & Ludo Waltman, 2016. "Clustering Scientific Publications Based on Citation Relations: A Systematic Comparison of Different Methods," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-23, April.
    17. Akshat Singhal & Song Cao & Christopher Churas & Dexter Pratt & Santo Fortunato & Fan Zheng & Trey Ideker, 2020. "Multiscale community detection in Cytoscape," PLOS Computational Biology, Public Library of Science, vol. 16(10), pages 1-10, October.
    18. Hao Wu & Lin Gao & Jihua Dong & Xiaofei Yang, 2014. "Detecting Overlapping Protein Complexes by Rough-Fuzzy Clustering in Protein-Protein Interaction Networks," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-13, March.
    19. Wang, Tai-Chi & Phoa, Frederick Kin Hing, 2016. "A scanning method for detecting clustering pattern of both attribute and structure in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 445(C), pages 295-309.
    20. Bingxue Qian & Ning Zhang, 2022. "Topology and Robustness of Weighted Air Transport Networks in Multi-Airport Region," Sustainability, MDPI, vol. 14(11), pages 1-15, June.

    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:566:y:2021:i:c:s0378437120309596. 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.