An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data
Lecture notes in computer sciencePublished 1 January 2000
Akihiro Inokuchi, Takashi Washio, Hiroshi Motoda
Citations1,029
SJR quartileQ2
SJR score0.35
SNIP0.55
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TL;DR
A novel approach named AGM to efficiently mine the association rules among the frequently appearing substructures in a given graph data set through the extended algorithm of the basket analysis is proposed.
Abstract
This paper proposes a novel approach named AGM to efficiently mine the association rules among the frequently appearing sub-structures in a given graph data set. A graph transaction is represented by an adjacency matrix, and the frequent patterns appearing in the matrices are mined through the extended algorithm of the basket analysis. Its performance has been evaluated for the artificial simulation data and the carcinogenesis data of Oxford University and NTP. Its high efficiency has been confirmed for the size of a real-world problem....
Keywords
Computer Science
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