DocumentCode :
3030950
Title :
Tuple Compress Based Outlier Detection on Uncertain Data of Mutually Exclusive Relation
Author :
He Mingke ; Ding Zheyuan ; Wen Ni
Author_Institution :
Sci. & Technol. on Inf. Syst. Eng. Lab., Nat. Univ. of Defense Technol., Changsha, China
fYear :
2013
fDate :
29-30 June 2013
Firstpage :
1631
Lastpage :
1634
Abstract :
Outlier detection techniques have widely been applied in medicine, finance, information security and so on. These techniques have been well studied on deterministic data. But, in some important application domains such as sensor networks, moving object tracking and data cleaning, uncertainty is inherent in data due to various factors. Furthermore, those uncertain data may have mutually exclusive relation. How to detect outliers on uncertain data of mutually exclusive relation is a new challenge. In this paper, a new definition of outlier on uncertain data is defined. A tuple compress based outlier detection method is proposed. Experimental results show that the proposed approach can efficiently detect outliers in data set.
Keywords :
data mining; uncertainty handling; data cleaning; deterministic data; finance; information security; medicine; moving object tracking; mutually exclusive relation; outlier detection techniques; sensor networks; tuple compress based outlier detection; uncertain data; Automation; Manufacturing; mutually exclusiverelation; outlier detection; uncertain data;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Manufacturing and Automation (ICDMA), 2013 Fourth International Conference on
Conference_Location :
Qingdao
Type :
conf
DOI :
10.1109/ICDMA.2013.391
Filename :
6598315
Link To Document :
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