Author :
Chen, Ming ; Chiang, I-Jen ; Lai, Chao-Wei
Abstract :
Frequent pattern mining is a hot topic in data mining field, and is now widely used in various areas. Cloud computing, a newly developed framework for parallel computing, offers great advantages over traditional parallel computing in big data processing. In this paper, we present a parallel frequent pattern mining for price fluctuation based on cloud computing. Firstly, original dataset is pre-processed and transformed to meet the requirement of frequent pattern mining model. Secondly, the mining task is described and multi-supports-based frequent pattern mining problem is defined. Finally, the experiment was carried out on a cluster of 12 computer nodes with map-reduce framework as a basis. The experimental results show that our approach can effectively find the frequent patterns in high efficiency, which can satisfy actual application.