• 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