Frequent pattern mining for price fluctuation based on cloud computing

Ming Chen; I. Jen Chiang; Chao Wei Lai

doi:10.1109/GrC.2012.6468561

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 proceeding › Conference 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 language	English
Title of host publication	Proceedings - 2012 IEEE International Conference on Granular Computing, GrC 2012
Pages	50-54
Number of pages	5
DOIs	https://doi.org/10.1109/GrC.2012.6468561
Publication status	Published - 2012
Externally published	Yes
Event	2012 IEEE International Conference on Granular Computing, GrC 2012 - HangZhou, China Duration: Aug 11 2012 → Aug 13 2012

Other

Other	2012 IEEE International Conference on Granular Computing, GrC 2012
Country/Territory	China
City	HangZhou
Period	8/11/12 → 8/13/12

ASJC Scopus subject areas

Software

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10.1109/GrC.2012.6468561

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title = "Frequent pattern mining for price fluctuation based on cloud computing",

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.",

author = "Ming Chen and Chiang, {I. Jen} and Lai, {Chao Wei}",

year = "2012",

doi = "10.1109/GrC.2012.6468561",

language = "English",

isbn = "9781467323093",

pages = "50--54",

booktitle = "Proceedings - 2012 IEEE International Conference on Granular Computing, GrC 2012",

note = "2012 IEEE International Conference on Granular Computing, GrC 2012 ; Conference date: 11-08-2012 Through 13-08-2012",

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TY - GEN

T1 - Frequent pattern mining for price fluctuation based on cloud computing

AU - Chen, Ming

AU - Chiang, I. Jen

AU - Lai, Chao Wei

PY - 2012

Y1 - 2012

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84875035441&partnerID=8YFLogxK

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U2 - 10.1109/GrC.2012.6468561

DO - 10.1109/GrC.2012.6468561

M3 - Conference contribution

AN - SCOPUS:84875035441

SN - 9781467323093

SP - 50

EP - 54

BT - Proceedings - 2012 IEEE International Conference on Granular Computing, GrC 2012

T2 - 2012 IEEE International Conference on Granular Computing, GrC 2012

Y2 - 11 August 2012 through 13 August 2012

ER -

Frequent pattern mining for price fluctuation based on cloud computing

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