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- W2384780139 abstract "In this paper, an algorithm is presented for mining frequent patterns based on a static IS- tree. The algorithm builds frequent patterns directly, instead of high-cost candidate sets generation- and-test method used by Apriori. It generates frequent patterns by depth first and pattern growth approach, and works on a static IS-tree, rather than a costly dynamic tree adopted by FP-growth. In order to reduce search space, it uses different filter technologies according to different characteristics of datasets. Our performance study and theory analysis show that it is efficient in both dense datasets and sparse datasets." @default.
- W2384780139 created "2016-06-24" @default.
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- W2384780139 date "2005-01-01" @default.
- W2384780139 modified "2023-09-28" @default.
- W2384780139 title "Mining Frequent Patterns Based on Static IS-Tree" @default.
- W2384780139 hasPublicationYear "2005" @default.
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