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  • Exploiting Vertex Relationships in Speeding up Subgraph Isomorphism over Large Graphs

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    Author(s)
    Ren, Xuguang
    Wang, Junhu
    Griffith University Author(s)
    Wang, John
    Year published
    2015
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    Abstract
    Subgraph Isomorphism is a fundamental problem in graph data processing. Most existing subgraph isomorphism algorithms are based on a backtracking framework which computes the solutions by incrementally matching all query vertices to candidate data vertices. However, we observe that extensive duplicate computation exists in these algorithms, and such duplicate computation can be avoided by exploiting relationships between data vertices. Motivated by this, we propose a novel approach, BoostIso, to reduce duplicate computation. Our extensive experiments with real datasets show that, after integrating our approach, most existing ...
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    Subgraph Isomorphism is a fundamental problem in graph data processing. Most existing subgraph isomorphism algorithms are based on a backtracking framework which computes the solutions by incrementally matching all query vertices to candidate data vertices. However, we observe that extensive duplicate computation exists in these algorithms, and such duplicate computation can be avoided by exploiting relationships between data vertices. Motivated by this, we propose a novel approach, BoostIso, to reduce duplicate computation. Our extensive experiments with real datasets show that, after integrating our approach, most existing subgraph isomorphism algorithms can be speeded up significantly, especially for some graphs with intensive vertex relationships, where the improvement can be up to several orders of magnitude.
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    Conference Title
    PROCEEDINGS OF THE VLDB ENDOWMENT
    Volume
    8
    Issue
    5
    DOI
    https://doi.org/10.14778/2735479.2735493
    Copyright Statement
    © The Author(s) 2015. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) License (http://creativecommons.org/licenses/by-nc-nd/3.0/) which permits unrestricted, non-commercial use, distribution and reproduction in any medium, providing that the work is properly cited.
    Subject
    Theory of computation
    Information systems
    Database systems
    Library and information studies
    Publication URI
    http://hdl.handle.net/10072/134181
    Collection
    • Conference outputs

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