DocumentCode :
3768442
Title :
Mining negative links between data clusters
Author :
Rifeng Wang; Gang Chen
Author_Institution :
College of Computer Science and Communication Engineering, Guangxi University of Science and Technology, Liu Zhou, 545006, China
fYear :
2015
Firstpage :
520
Lastpage :
523
Abstract :
Link discovery (LD) is an important task in data mining for identifying interactions between data groups, or relating in society community networks. A new strategy is designed for mining a new kind of link: negative links between data clusters. The efficiency is gained by pruning strong positive relative items. Negative item is computing with correlation coefficient. The number of the negative item correlation is used to identify the negative links between clusters. These negative links are extremely useful in business fraud, medical treatment and incursion detection. Experiments on real datasets illustrate that our approach is efficient and promising.
Publisher :
ieee
Conference_Titel :
Communication Problem-Solving (ICCP), 2015 IEEE International Conference on
Print_ISBN :
978-1-4673-6543-7
Type :
conf
DOI :
10.1109/ICCPS.2015.7454219
Filename :
7454219
Link To Document :
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