Structural graph indexing for mining complex networks

Hakan Kardeş, Mehmet Hadi Güneş

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    3 Scopus citations

    Abstract

    Systems such as proteins, chemical compounds, and the Internet are being modeled as complex networks to identify local and global characteristics of the system. In many instances, these graphs are very large in size presenting challenges in their analysis. Hence, graph indexing techniques are developed to enhance various graph mining algorithms. In this paper, we propose a new Structural Graph Indexing (SGI) technique that does not limit the number of nodes in indexing to provide an alternative tool for graph mining algorithms. As indexing feature, we use common graph structures, namely, star, complete bipartite, triangle and clique, that frequently appear in protein, chemical compound, and Internet graphs. Note that, SGI lists all substructures matching structure formulations and other graph structures can be identified and added to the SGI.

    Original languageEnglish
    Title of host publicationProceedings - 2010 IEEE 30th International Conference on Distributed Computing Systems Workshops, ICDCSW 2010
    Pages99-104
    Number of pages6
    DOIs
    StatePublished - 2010
    Event2010 IEEE 30th International Conference on Distributed Computing Systems Workshops, ICDCSW 2010 - Genova, Italy
    Duration: 21 Jun 201025 Jun 2010

    Publication series

    NameProceedings - International Conference on Distributed Computing Systems

    Conference

    Conference2010 IEEE 30th International Conference on Distributed Computing Systems Workshops, ICDCSW 2010
    Country/TerritoryItaly
    CityGenova
    Period21/06/1025/06/10

    Keywords

    • Complex networks
    • Graph indexing
    • Graph mining
    • Structural graph indexing

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