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- W4224132013 abstract "In data mining, association-rules mining are a crucial technology. The Frequent-Growth (FP) algorithm is a well-known algorithm for association mining. However, FP-Growth method in mining requires two scans of the database which affects the process's efficiency. We have compared two different FP-Growth algorithms namely Painting-Growth algorithm as well as not Painting-Growth algorithm via the study of association mining and FP-Growth algorithm. With the FP-Growth algorithm, we have compared two different types of enhanced algorithms. Performance of these enhanced algorithms is absolutely better than FP-Growth algorithm, according to the experimental results. Painting-Growth algorithm has a data volume of greater than 1050 and also, N Painting-Growth algorithm has a data volume of less than 10000." @default.
- W4224132013 created "2022-04-20" @default.
- W4224132013 creator A5008366217 @default.
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- W4224132013 date "2022-01-28" @default.
- W4224132013 modified "2023-10-01" @default.
- W4224132013 title "Performance Analysis on Advances in Frequent Pattern Growth Algorithm" @default.
- W4224132013 cites W1951217842 @default.
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- W4224132013 doi "https://doi.org/10.1109/accai53970.2022.9752650" @default.
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