Title :
Distance 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
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 distance-based outlier detection method is proposed. Experimental results show that the proposed approach can efficiently detect outliers in data set.
Keywords :
data handling; data mining; uncertainty handling; data cleaning; deterministic data; distance-based outlier detection method; dstance based outlier detection; finance; information security; medicine; moving object tracking; mutually exclusive relation; sensor networks; uncertain data; Algorithm design and analysis; Data models; Databases; Equations; Probabilistic logic; Reliability; Vectors; mutually exclusive relation; outlier detection; uncertain data;
Conference_Titel :
Signal Processing, Communication and Computing (ICSPCC), 2013 IEEE International Conference on
Conference_Location :
KunMing
DOI :
10.1109/ICSPCC.2013.6663973