Top-Down Algorithm for Mining Maximal Frequent Subgraph

Jing Feng Guo; Ran Chai; Jia Li

doi:10.4028/www.scientific.net/AMR.204-210.1472

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 204-210Top-Down Algorithm for Mining Maximal Frequent...

Top-Down Algorithm for Mining Maximal Frequent Subgraph

Abstract:

In order to solution the problem of mining maximal frequent subgraph is very hard we proposed new algorithm Top-Down. The process of this algorithm is using decision tree to count support then firstly judge the biggest graph whether frequent and gradually reduce the graph which used to judge until can not mining maximal frequent subgraph, at the same time this algorithm is proposed a theorem and two principles these are improved the mining efficiency.

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Periodical:

Advanced Materials Research (Volumes 204-210)

Pages:

1472-1476

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.204-210.1472

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Online since:

February 2011

Authors:

Jing Feng Guo, Ran Chai, Jia Li

Keywords:

Data Mining (DM), Decision Tree, Maximal Frequent Subgraph Mining, Support, Top-Down Algorithm

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