Efficient Mining of Frequent Subgraphs in the Presence of Isomorphism
ICDM(2003)
摘要
Frequent subgraph mining is an active research topic inthe data mining community. A graph is a general modelto represent data and has been used in many domains likecheminformatics and bioinformatics. Mining patterns fromgraph databases is challenging since graph related operations,such as subgraph testing, generally have higher timecomplexity than the corresponding operations on itemsets,sequences, and trees, which have been studied extensively.In this paper, we propose a novel frequent subgraph miningalgorithm: FFSM, which employs a vertical search schemewithin an algebraic graph framework we have developedto reduce the number of redundant candidates proposed.Our empirical study on synthetic and real datasets demonstratesthat FFSM achieves a substantial performance gainover the current start-of-the-art subgraph mining algorithmgSpan.
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关键词
data mining community,current start-of-the-art subgraph mining,frequent subgraphs,domains likecheminformatics,mining patterns fromgraph databases,subgraph testing,efficient mining,active research topic inthe,novel frequent subgraph miningalgorithm,frequent subgraph mining,corresponding operation,algebraic graph framework,time complexity,data mining,empirical study,graph theory
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