MISFP-Growth: Hadoop-Based Frequent Pattern Mining with Multiple Item Support
In practice, single item support cannot comprehensively address the complexity of items in large datasets. In this study, we propose a big data analytics framework (named Multiple Item Support Frequent Patterns, MISFP-growth algorithm) that uses Hadoop-based parallel computing to achieve high-effici...
Main Authors: | Chen-Shu Wang, Jui-Yen Chang |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2019-05-01
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Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/9/10/2075 |
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