Parallelizing the improved algorithm for frequent patterns mining problem

Authors:
Thanh-Trung Nguyen;Bach-Hien Nguyen;Phi-Khu Nguyen
Affiliations:
Department of Computer Science, University of Information Technology, Vietnam National University, HCM City, Vietnam;Department of Computer Science, University of Information Technology, Vietnam National University, HCM City, Vietnam;Department of Computer Science, University of Information Technology, Vietnam National University, HCM City, Vietnam
Venue:
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part I
Year:
2013

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Abstract

Mining frequent pattern has been studied for a long time. There were many algorithms introduced and proved their efficiency. But most of them have to rebuild the frequent patterns every time when there are some changes (insert, update or delete) in dataset. Accumulated Frequent Pattern has been introduced recently. It updates existing frequent patterns when there are any changes. But the time complexity is so high. This paper introduces two ways to parallelize the Accumulated Frequent Pattern algorithm and reduce the time complexity.