gSpan: Graph-Based Substructure Pattern Mining

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gSpan: Graph-Based Substructure Pattern Mining (2002)

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by Xifeng Yan , Jiawei Han

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BibTeX

@MISC{Yan02gspan:graph-based,
    author = {Xifeng Yan and Jiawei Han},
    title = {gSpan: Graph-Based Substructure Pattern Mining},
    year = {2002}
}

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Abstract

We investigate new approaches for frequent graph-based pattern mining in graph datasets and propose a novel algorithm called gSpan (graph-based Substructure pattern mining) , which discovers frequent substructures without candidate generation. gSpan builds a new lexicographic order among graphs, and maps each graph to a unique minimum DFS code as its canonical label. Based on this lexicographic order, gSpan adopts the depth-first search strategy to mine frequent connected subgraphs efficiently. Our performance study shows that gSpan substantially outperforms previous algorithms, sometimes by an order of magnitude.

Keyphrases

graph-based substructure pattern mining frequent substructure depth-first search strategy frequent graph-based pattern mining canonical label lexicographic order graph datasets new approach unique minimum dfs code previous algorithm new lexicographic order performance study candidate generation novel algorithm

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