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  • Efficient subgraph matching using topological node feature constraints

    Author(s)
    Dahm, Nicholas
    Bunke, Horst
    Caelli, Terry
    Gao, Yongsheng
    Griffith University Author(s)
    Gao, Yongsheng
    Year published
    2015
    Metadata
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    Abstract
    This paper presents techniques designed to minimise the number of states which are explored during subgraph isomorphism detection. A set of advanced topological node features, calculated from n-neighbourhood graphs, is presented and shown to outperform existing features. Further, the pruning effectiveness of both the new and existing topological node features is significantly improved through the introduction of strengthening techniques. In addition to topological node features, these strengthening techniques can also be used to enhance application-specific node labels using a proposed novel extension to existing pruning ...
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    This paper presents techniques designed to minimise the number of states which are explored during subgraph isomorphism detection. A set of advanced topological node features, calculated from n-neighbourhood graphs, is presented and shown to outperform existing features. Further, the pruning effectiveness of both the new and existing topological node features is significantly improved through the introduction of strengthening techniques. In addition to topological node features, these strengthening techniques can also be used to enhance application-specific node labels using a proposed novel extension to existing pruning algorithms. Through the combination of these techniques, the number of explored search states can be reduced to near-optimal levels.
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    Journal Title
    Pattern Recognition
    Volume
    48
    Issue
    2
    DOI
    https://doi.org/10.1016/j.patcog.2014.05.018
    Subject
    Information systems
    Other information and computing sciences not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/141113
    Collection
    • Journal articles

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