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Published in:
2010 | OriginalPaper | Chapter
Attribute Reduction for Massive Data Based on Rough Set Theory and MapReduce
Authors : Yong Yang, Zhengrong Chen, Zhu Liang, Guoyin Wang
Published in: Rough Set and Knowledge Technology
Publisher: Springer Berlin Heidelberg
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Data processing and knowledge discovery for massive data is always a hot topic in data mining, along with the era of cloud computing is coming, data mining for massive data is becoming a highlight research topic. In this paper, attribute reduction for massive data based on rough set theory is studied. The parallel programming mode of MapReduce is introduced and combined with the attribute reduction algorithm of rough set theory, a parallel attribute reduction algorithm based on MapReduce is proposed, experiment results show that the proposed method is more efficiency for massive data mining than traditional method, and it is a effective method effective method effective method for data mining on cloud computing platform.