Frequent pattern mining for price fluctuation based on cloud computing

Ming Chen, I. Jen Chiang, Chao Wei Lai

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationProceedings - 2012 IEEE International Conference on Granular Computing, GrC 2012
Pages50-54
Number of pages5
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 IEEE International Conference on Granular Computing, GrC 2012 - HangZhou, China
Duration: Aug 11 2012Aug 13 2012

Other

Other2012 IEEE International Conference on Granular Computing, GrC 2012
CountryChina
CityHangZhou
Period8/11/128/13/12

ASJC Scopus subject areas

  • Software

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  • Cite this

    Chen, M., Chiang, I. J., & Lai, C. W. (2012). Frequent pattern mining for price fluctuation based on cloud computing. In Proceedings - 2012 IEEE International Conference on Granular Computing, GrC 2012 (pp. 50-54). [6468561] https://doi.org/10.1109/GrC.2012.6468561