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...

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Bibliographic Details
Main Authors: Chen-Shu Wang, Jui-Yen Chang
Format: Article
Language:English
Published: MDPI AG 2019-05-01
Series:Applied Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3417/9/10/2075