IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v557y2020ics0378437120305112.html
   My bibliography  Save this article

Link prediction using node information on local paths

Author

Listed:
  • Aziz, Furqan
  • Gul, Haji
  • Muhammad, Ishtiaq
  • Uddin, Irfan

Abstract

Link prediction is one of the most important and challenging tasks in complex network analysis, which aims to predict missing link based on existing ones in a network. This problem is of both theoretical interest and has applications in diverse scientific disciplines, including social network analysis, recommendation systems, and biological networks. In this paper we propose a novel link prediction method that aims at improving the accuracy of existing path-based methods by incorporating information about the nodes along local paths. We investigate the proposed framework empirically and conduct extensive experiments on real-world datasets obtained from diverse domains. Results show that the proposed method has achieved increased prediction accuracy when compared to existing state-of-the-art link prediction methods.

Suggested Citation

  • Aziz, Furqan & Gul, Haji & Muhammad, Ishtiaq & Uddin, Irfan, 2020. "Link prediction using node information on local paths," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 557(C).
    • Handle: RePEc:eee:phsmap:v:557:y:2020:i:c:s0378437120305112
    DOI: 10.1016/j.physa.2020.124980
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437120305112
    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.2020.124980?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. Wei, Dong & Zhou, Tao & Cimini, Giulio & Wu, Pei & Liu, Weiping & Zhang, Yi-Cheng, 2011. "Effective mechanism for social recommendation of news," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(11), pages 2117-2126.
    2. Hadas, Yuval & Gnecco, Giorgio & Sanguineti, Marcello, 2017. "An approach to transportation network analysis via transferable utility games," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 120-143.
    3. Zhang, Peng & Qiu, Dan & Zeng, An & Xiao, Jinghua, 2018. "A comprehensive comparison of network similarities for link prediction and spurious link elimination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 500(C), pages 97-105.
    4. István A. Kovács & Katja Luck & Kerstin Spirohn & Yang Wang & Carl Pollis & Sadie Schlabach & Wenting Bian & Dae-Kyum Kim & Nishka Kishore & Tong Hao & Michael A. Calderwood & Marc Vidal & Albert-Lász, 2019. "Network-based prediction of protein interactions," Nature Communications, Nature, vol. 10(1), pages 1-8, December.
    5. Aaron Clauset & Cristopher Moore & M. E. J. Newman, 2008. "Hierarchical structure and the prediction of missing links in networks," Nature, Nature, vol. 453(7191), pages 98-101, May.
    6. 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.
    7. Tao Zhou & Linyuan Lü & Yi-Cheng Zhang, 2009. "Predicting missing links via local information," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 71(4), pages 623-630, October.
    8. Guo, Lin & Zhang, Ben, 2019. "Mining structural influence to analyze relationships in social network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 301-309.
    9. Gao, Hua & Huang, Jianbin & Cheng, Qiang & Sun, Heli & Wang, Baoli & Li, He, 2019. "Link prediction based on linear dynamical response," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 527(C).
    10. Leo Katz, 1953. "A new status index derived from sociometric analysis," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 39-43, March.
    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. Yuliansyah, Herman & Othman, Zulaiha Ali & Bakar, Azuraliza Abu, 2023. "A new link prediction method to alleviate the cold-start problem based on extending common neighbor and degree centrality," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 616(C).

    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. Lee, Yan-Li & Zhou, Tao, 2021. "Collaborative filtering approach to link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 578(C).
    2. Zhou, Tao & Lee, Yan-Li & Wang, Guannan, 2021. "Experimental analyses on 2-hop-based and 3-hop-based link prediction algorithms," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 564(C).
    3. Lee, Yan-Li & Dong, Qiang & Zhou, Tao, 2021. "Link prediction via controlling the leading eigenvector," Applied Mathematics and Computation, Elsevier, vol. 411(C).
    4. Wang, Zuxi & Wu, Yao & Li, Qingguang & Jin, Fengdong & Xiong, Wei, 2016. "Link prediction based on hyperbolic mapping with community structure for complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 450(C), pages 609-623.
    5. Yu, Jiating & Wu, Ling-Yun, 2022. "Multiple Order Local Information model for link prediction in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    6. Liu, Shuxin & Ji, Xinsheng & Liu, Caixia & Bai, Yi, 2017. "Extended resource allocation index for link prediction of complex network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 479(C), pages 174-183.
    7. Sherkat, Ehsan & Rahgozar, Maseud & Asadpour, Masoud, 2015. "Structural link prediction based on ant colony approach in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 80-94.
    8. Zhou, Tao, 2023. "Discriminating abilities of threshold-free evaluation metrics in link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 615(C).
    9. Kumar, Ajay & Singh, Shashank Sheshar & Singh, Kuldeep & Biswas, Bhaskar, 2020. "Link prediction techniques, applications, and performance: A survey," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    10. Chunning Wang & Fengqin Tang & Xuejing Zhao, 2023. "LPGRI: A Global Relevance-Based Link Prediction Approach for Multiplex Networks," Mathematics, MDPI, vol. 11(14), pages 1-15, July.
    11. Wu, Jiehua & Shen, Jing & Zhou, Bei & Zhang, Xiayan & Huang, Bohuai, 2019. "General link prediction with influential node identification," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 996-1007.
    12. Xu-Wen Wang & Lorenzo Madeddu & Kerstin Spirohn & Leonardo Martini & Adriano Fazzone & Luca Becchetti & Thomas P. Wytock & István A. Kovács & Olivér M. Balogh & Bettina Benczik & Mátyás Pétervári & Be, 2023. "Assessment of community efforts to advance network-based prediction of protein–protein interactions," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    13. Yao, Yabing & Zhang, Ruisheng & Yang, Fan & Tang, Jianxin & Yuan, Yongna & Hu, Rongjing, 2018. "Link prediction in complex networks based on the interactions among paths," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 52-67.
    14. Pei, Panpan & Liu, Bo & Jiao, Licheng, 2017. "Link prediction in complex networks based on an information allocation index," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 470(C), pages 1-11.
    15. Zhang, Xue & Wang, Xiaojie & Zhao, Chengli & Yi, Dongyun & Xie, Zheng, 2014. "Degree-corrected stochastic block models and reliability in networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 553-559.
    16. Chi, Kuo & Qu, Hui & Yin, Guisheng, 2022. "Link prediction for existing links in dynamic networks based on the attraction force," Chaos, Solitons & Fractals, Elsevier, vol. 159(C).
    17. Wang, Xiaojie & Zhang, Xue & Zhao, Chengli & Xie, Zheng & Zhang, Shengjun & Yi, Dongyun, 2015. "Predicting link directions using local directed path," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 260-267.
    18. Park, Ji Hwan & Chang, Woojin & Song, Jae Wook, 2020. "Link prediction in the Granger causality network of the global currency market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 553(C).
    19. Wang, Jun & Zhang, Qian-Ming & Zhou, Tao, 2019. "Tag-aware link prediction algorithm in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 523(C), pages 105-111.
    20. Liao, Hao & Zeng, An & Zhang, Yi-Cheng, 2015. "Predicting missing links via correlation between nodes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 436(C), pages 216-223.

    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:557:y:2020:i:c:s0378437120305112. 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.