Algorithms that can accurately determine the similarity of directed graphs often need a heavy overhead. In order to save time and achieve a better balance between performance cost and accuracy, this paper proposes a novel two-stage similarity determination algorithm for directed graphs. The algorithm includes two stages. The first is called as features similarity determination, and the second is called as structural similarity determination. The former can quickly determine the similarity through the general features of directed graphs, and eliminate obviously dissimilar graphs, thus reducing the time cost in total. On the basis of the former filtering result, the similarity determination is further made from the graphic structure to ensure the accuracy of similarity determination. Our test and analysis show that the algorithm can achieve a good balance between accuracy and performance.


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    Titel :

    A Novel Two-Stage Directed Graph Similarity Determination Algorithm


    Beteiligte:
    Hongwei, Zhou (Autor:in) / Xiaojie, Huang (Autor:in) / Zhipeng, Ke (Autor:in) / Yuchen, Zhang (Autor:in) / Jinhui, Yuan (Autor:in)


    Erscheinungsdatum :

    12.10.2022


    Format / Umfang :

    1100204 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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