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TBSGM: A Fast Subgraph Matching Method on Large Scale Graphs

Author

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  • Fusheng Jin

    (Beijing Institute of Technology, Beijing, China)

  • Yifeng Yang

    (Beijing Institute of Technology, Beijing, China)

  • Shuliang Wang

    (School of Software, Beijing Institute of Technology, Beijing, China)

  • Ye Xue

    (Northwestern University, Evanston, USA)

  • Zhen Yan

    (Technical University of Munich, Munich, Germany)

Abstract

Subgraph matching, which belongs to NP-hard, faces significant challenges on a large scale graph with billions of nodes, and existing methods are usually confronted with greater challenges from both stability and efficiency. In this article, a subgraph matching method in a distributed system, tree model-based subgraph matching method (TBSGM) is proposed. The authors provide a transformed efficient query tree as a replacement for a query graph. In order to get the tree, they present a cost evaluation model which may help to generate the efficient query tree according to network communication-cost and calculation-cost evaluation. Also, a key set based indexing strategy for intermediate results is given to simplify the matching results during network communication. Extensive experiments with real-world datasets show that TBSGM significantly outperforms other methods in the aspects of scalability and efficiency.

Suggested Citation

  • Fusheng Jin & Yifeng Yang & Shuliang Wang & Ye Xue & Zhen Yan, 2018. "TBSGM: A Fast Subgraph Matching Method on Large Scale Graphs," International Journal of Data Warehousing and Mining (IJDWM), IGI Global, vol. 14(4), pages 67-89, October.
    • Handle: RePEc:igg:jdwm00:v:14:y:2018:i:4:p:67-89
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