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REGAL: Representation Learning-based Graph Alignment

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Danai KoutraAuthors Info & Claims

CIKM '18: Proceedings of the 27th ACM International Conference on Information and Knowledge Management

Pages 117 - 126

https://doi.org/10.1145/3269206.3271788

Published: 17 October 2018 Publication History

Abstract

Problems involving multiple networks are prevalent in many scientific and other domains. In particular, network alignment, or the task of identifying corresponding nodes in different networks, has applications across the social and natural sciences. Motivated by recent advancements in node representation learning for single-graph tasks, we propose REGAL (REpresentation learning-based Graph ALignment), a framework that leverages the power of automatically-learned node representations to match nodes across different graphs. Within REGAL we devise xNetMF, an elegant and principled node embedding formulation that uniquely generalizes to multi-network problems. Our results demonstrate the utility and promise of unsupervised representation learning-based network alignment in terms of both speed and accuracy. REGAL runs up to 30x faster in the representation learning stage than comparable methods, outperforms existing network alignment methods by 20 to 30% accuracy on average, and scales to networks with millions of nodes each.

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Cited By

Tang RYong ZJiang SChen XLiu YZhang YSun GWang W(2025)Network alignmentPhysics Reports10.1016/j.physrep.2024.11.0061107(1-45)Online publication date: Mar-2025
https://doi.org/10.1016/j.physrep.2024.11.006
Li YZhang LQian F(2024)Improving Unsupervised Network Alignment with Matched Neighborhood ConsistencyMathematics10.3390/math1208121112:8(1211)Online publication date: 17-Apr-2024
https://doi.org/10.3390/math12081211
Huang SXiang HLeng CXiao F(2024)Cross-Social-Network User Identification Based on Bidirectional GCN and MNF-UI ModelsElectronics10.3390/electronics1312235113:12(2351)Online publication date: 15-Jun-2024
https://doi.org/10.3390/electronics13122351
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Index Terms

REGAL: Representation Learning-based Graph Alignment
1. Computing methodologies
  1. Machine learning
    1. Machine learning approaches
      1. Learning latent representations
2. Information systems
  1. Information systems applications
    1. Data mining

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cover image ACM Conferences

CIKM '18: Proceedings of the 27th ACM International Conference on Information and Knowledge Management

October 2018

2362 pages

ISBN:9781450360142

DOI:10.1145/3269206

General Chair:
Alfredo Cuzzocrea
University of Trieste, Italy
,
Program Chairs:
James Allan
University of Massachusetts, USA
,
Norman Paton
University of Manchester, United Kingdom
,
Divesh Srivastava
AT&T Labs Research, USA
,
Rakesh Agrawal
Data Insights Lab, USA
,
Andrei Broder
Google Research, USA
,
Mohammed Zaki
Rensselaer Polytechnic Institute, USA
,
Selcuk Candan
Arizona State University, USA
,
Alexandros Labrinidis
University of Pittsburgh, USA
,
Assaf Schuster
Technion, Israel
,
Haixun Wang
Google Research, USA

Copyright © 2018 ACM.

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Published: 17 October 2018

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CIKM '18: The 27th ACM International Conference on Information and Knowledge Management

October 22 - 26, 2018

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CIKM '18 Paper Acceptance Rate 147 of 826 submissions, 18%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

Tang RYong ZJiang SChen XLiu YZhang YSun GWang W(2025)Network alignmentPhysics Reports10.1016/j.physrep.2024.11.0061107(1-45)Online publication date: Mar-2025
https://doi.org/10.1016/j.physrep.2024.11.006
Li YZhang LQian F(2024)Improving Unsupervised Network Alignment with Matched Neighborhood ConsistencyMathematics10.3390/math1208121112:8(1211)Online publication date: 17-Apr-2024
https://doi.org/10.3390/math12081211
Huang SXiang HLeng CXiao F(2024)Cross-Social-Network User Identification Based on Bidirectional GCN and MNF-UI ModelsElectronics10.3390/electronics1312235113:12(2351)Online publication date: 15-Jun-2024
https://doi.org/10.3390/electronics13122351
Xie XZang WHu YJi JXiong Z(2024)Novel Method of Edge-Removing Walk for Graph Representation in User Identity LinkageElectronics10.3390/electronics1304071513:4(715)Online publication date: 9-Feb-2024
https://doi.org/10.3390/electronics13040715
Liu WZhang WZhao HJin Z(2024)GABoost: Graph Alignment Boosting via Local Optimum EscapeProceedings of the ACM on Management of Data10.1145/36771352:4(1-26)Online publication date: 30-Sep-2024
https://dl.acm.org/doi/10.1145/3677135
Xu HXiang LGan XFu LWang XZhou C(2024)Distributional Learning for Network Alignment with Global ConstraintsACM Transactions on Knowledge Discovery from Data10.1145/363805618:4(1-16)Online publication date: 12-Feb-2024
https://dl.acm.org/doi/10.1145/3638056
Do MShin KBaeza-Yates RBonchi F(2024)Unsupervised Alignment of Hypergraphs with Different ScalesProceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3637528.3671955(609-620)Online publication date: 25-Aug-2024
https://dl.acm.org/doi/10.1145/3637528.3671955
Seo DLim JShin WKim SSerra ESpezzano F(2024)Leveraging Trustworthy Node Attributes for Effective Network AlignmentProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679658(2004-2013)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3679658
Yan YHu YZhou QWu SWang DTong HSerra ESpezzano F(2024)Topological Anonymous Walk Embedding: A New Structural Node Embedding ApproachProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3679565(2796-2806)Online publication date: 21-Oct-2024
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Lan LWang PShi RLiu TZeng JSun FRen YTao JGuan XHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)Grand: A Fast and Accurate Graph Retrieval Framework via Knowledge DistillationProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657773(1639-1648)Online publication date: 10-Jul-2024
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