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Hierarchical All-Pairs SimRank Calculation

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Database Systems for Advanced Applications (DASFAA 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13945))

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Abstract

All-pairs SimRank calculation is a classic SimRank problem. However, all-pairs algorithms suffer from efficiency issues and accuracy issues. In this paper, we convert the non-linear simrank calculation into a new simple closed formulation of linear system. And we come up with a sequence of novel algorithms to efficiently solve the linear system with accuracy guarantees. To reduce the memory consumption and improve the computational efficiency, we build a hierarchical framework to calculate the all-pairs SimRank scores, which includes locally coarse calculation and globally refine calculation. We first solve the local linear systems generated from the subgraphs, then we refine the SimRank scores on the full graph from the residuals of the local structures. We also show that our algorithms outperform the state-of-the-art all-pairs SimRank computation algorithms on real graphs.

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Notes

  1. 1.

    http://glaros.dtc.umn.edu/gkhome/views/metis.

  2. 2.

    http://snap.stanford.edu/data/index.html.

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Acknowledgements

This work is supported by National Natural Science Foundation of China under the grant No. 62072460, 62076245, 62172424, 62276270, and Beijing Natural Science Foundation (4212022).

Author information

Authors and Affiliations

  1. Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education, School of Information, Renmin University of China, Beijing, China

    Liangfu Zhang, Cuiping Li, Xue Zhang & Hong Chen

Authors
  1. Liangfu Zhang
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  2. Cuiping Li
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  3. Xue Zhang
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  4. Hong Chen
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Corresponding author

Correspondence to Cuiping Li .

Editor information

Editors and Affiliations

  1. Tianjin University, Tianjin, China

    Xin Wang

  2. University of Torino, Turin, Italy

    Maria Luisa Sapino

  3. POSTECH, Pohang, Korea (Republic of)

    Wook-Shin Han

  4. University of California Santa Barbara, Santa Barbara, CA, USA

    Amr El Abbadi

  5. University of Auckland, Auckland, New Zealand

    Gill Dobbie

  6. Tianjin University, Tianjin, China

    Zhiyong Feng

  7. Beijing University of Posts and Telecommunications, Beijing, China

    Yingxiao Shao

  8. The University of Queensland, Brisbane, QLD, Australia

    Hongzhi Yin

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Zhang, L., Li, C., Zhang, X., Chen, H. (2023). Hierarchical All-Pairs SimRank Calculation. In: Wang, X., et al. Database Systems for Advanced Applications. DASFAA 2023. Lecture Notes in Computer Science, vol 13945. Springer, Cham. https://doi.org/10.1007/978-3-031-30675-4_17

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  • DOI: https://doi.org/10.1007/978-3-031-30675-4_17

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-30674-7

  • Online ISBN: 978-3-031-30675-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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