DocumentCode
235022
Title
A Parallel Method for Rough Entropy Computation Using MapReduce
Author
Si-Yuan Jing ; Jin Yang ; Kun She
Author_Institution
Sch. of Comput. Sci., Leshan Normal Univ., Leshan, China
fYear
2014
fDate
15-16 Nov. 2014
Firstpage
707
Lastpage
710
Abstract
Rough set theory has been proven to be a successful computational intelligence tool. Rough entropy is a basic concept in rough set theory and it is usually used to measure the roughness of information set. Existing algorithms can only deal with small data set. Therefore, this paper proposes a method for parallel computation of entropy using MapReduce, which is hot in big data mining. Moreover, corresponding algorithm is also put forward to handle big data set. Experimental results show that the proposed parallel method is effective.
Keywords
Big Data; data mining; entropy; mathematics computing; parallel programming; rough set theory; MapReduce; big data mining; big data set handling; computational intelligence tool; information set roughness measurement; parallel computation method; rough entropy computation; rough set theory; Big data; Clustering algorithms; Computers; Data mining; Entropy; Information entropy; Set theory; Data Mining; Entropy; Hadoop; MapReduce; Rough set theory;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Security (CIS), 2014 Tenth International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4799-7433-7
Type
conf
DOI
10.1109/CIS.2014.41
Filename
7016989
Link To Document