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Efficient Graph Sequence Mining Using Reverse Search Akihiro INOKUCHI Hiroaki IKUTA Takashi WASHIO Publication IEICE TRANSACTIONS on Information and Systems Vol.E95-D No.7 pp.1947-1958 Publication Date: 2012/07/01 Online ISSN: 1745-1361 DOI: 10.1587/transinf.E95.D.1947 Print ISSN: 0916-8532 Type of Manuscript: PAPER Category: Artificial Intelligence, Data Mining Keyword: frequent pattern, graph sequence, reverse search, Full Text: PDF(467.8KB)>>
Summary: The mining of frequent subgraphs from labeled graph data has been studied extensively. Furthermore, much attention has recently been paid to frequent pattern mining from graph sequences. A method, called GTRACE, has been proposed to mine frequent patterns from graph sequences under the assumption that changes in graphs are gradual. Although GTRACE mines the frequent patterns efficiently, it still needs substantial computation time to mine the patterns from graph sequences containing large graphs and long sequences. In this paper, we propose a new version of GTRACE that permits efficient mining of frequent patterns based on the principle of a reverse search. The underlying concept of the reverse search is a general scheme for designing efficient algorithms for hard enumeration problems. Our performance study shows that the proposed method is efficient and scalable for mining both long and large graph sequence patterns and is several orders of magnitude faster than the original GTRACE. | ||||||||||
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