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Using community information to improve the precision of link prediction methods

Authors:

Sucheta Soundarajan,

John HopcroftAuthors Info & Claims

WWW '12 Companion: Proceedings of the 21st International Conference on World Wide Web

Pages 607 - 608

https://doi.org/10.1145/2187980.2188150

Published: 16 April 2012 Publication History

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Abstract

Because network data is often incomplete, researchers consider the link prediction problem, which asks which non-existent edges in an incomplete network are most likely to exist in the complete network. Classical approaches compute the 'similarity' of two nodes, and conclude that highly similar nodes are most likely to be connected in the complete network. Here, we consider several such similarity-based measures, but supplement the similarity calculations with community information. We show that for many networks, the inclusion of community information improves the accuracy of similarity-based link prediction methods.

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Index Terms

Using community information to improve the precision of link prediction methods
1. Information systems
  1. Information storage systems
    1. Storage architectures
      1. Storage network architectures

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Information & Contributors

Information

Published In

WWW '12 Companion: Proceedings of the 21st International Conference on World Wide Web

April 2012

1250 pages

ISBN:9781450312301

DOI:10.1145/2187980

General Chairs:
Alain Mille
Université de Lyon, France
,
Fabien Gandon
INRIA, France
,
Jacques Misselis
HP, France
,
Program Chairs:
Michael Rabinovich
Case Western Reserve University, USA
,
Steffen Staab
University of Koblenz-Landau, Germany

In-Cooperation

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2012

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WWW 2012

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Univ. de Lyon

WWW 2012: 21st World Wide Web Conference 2012

April 16 - 20, 2012

Lyon, France

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Ishii CAsatani KSakata I(2024)Detecting possible pairs of materials for composites using a material word co-occurrence networkPLOS ONE10.1371/journal.pone.029736119:1(e0297361)Online publication date: 26-Jan-2024
https://doi.org/10.1371/journal.pone.0297361
Liu ZJi FYang JCao XZhang MChen HChang Y(2024)Refining Euclidean Obfuscatory Nodes Helps: A Joint-Space Graph Learning Method for Graph Neural NetworksIEEE Transactions on Neural Networks and Learning Systems10.1109/TNNLS.2024.340589835:9(11720-11733)Online publication date: Sep-2024
https://doi.org/10.1109/TNNLS.2024.3405898
Soares NBraga RDavid JSiqueira KStroele V(2024)An approach to foster agribusiness marketing applying data analysis of social networkComputers and Electronics in Agriculture10.1016/j.compag.2024.109044222(109044)Online publication date: Jul-2024
https://doi.org/10.1016/j.compag.2024.109044
Yang JWu Y(2024)Link prediction based on depth structure in social networksInternational Journal of Machine Learning and Cybernetics10.1007/s13042-024-02178-415:10(4639-4657)Online publication date: 14-May-2024
https://doi.org/10.1007/s13042-024-02178-4
Feng ZQiao MCheng H(2023)Modularity-based Hypergraph Clustering: Random Hypergraph Model, Hyperedge-cluster Relation, and ComputationProceedings of the ACM on Management of Data10.1145/36173351:3(1-25)Online publication date: 13-Nov-2023
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Wang HCui ZLiu RFang LSha Y(2023)A Multi-Type Transferable Method for Missing Link Prediction in Heterogeneous Social NetworksIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.323348135:11(10981-10991)Online publication date: 1-Nov-2023
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Toprak MBoldrini CPassarella AConti M(2023)Harnessing the Power of Ego Network Layers for Link Prediction in Online Social NetworksIEEE Transactions on Computational Social Systems10.1109/TCSS.2022.315594610:1(48-60)Online publication date: Feb-2023
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Zhang HJayaweera MRen BWang YSoundarajan S(2023)Unfairness in Distributed Graph Frameworks2023 IEEE International Conference on Data Mining (ICDM)10.1109/ICDM58522.2023.00203(1529-1534)Online publication date: 1-Dec-2023
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Kerkache MSadeg-Belkacem LBenbouzid-Si Tayeb F(2023)A hybrid approach for enhanced link prediction in social networks based on community detectionInternational Journal of General Systems10.1080/03081079.2023.226504353:2(154-183)Online publication date: 10-Oct-2023
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Kerkache HSadeg-Belkacem LTayeb F(2023)Improved artificial bee colony algorithm based on community detection for link prediction problemMultimedia Tools and Applications10.1007/s11042-023-17197-683:14(41655-41681)Online publication date: 13-Oct-2023
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HM-EIICT: Fairness-aware link prediction in complex networks using community information

h-Index-based link prediction methods in citation network

Link prediction using time series of neighborhood-based node similarity scores

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