• DocumentCode
    2646709
  • Title

    Research of Gravity-Based Outliers Detection

  • Author

    Jianliang Meng ; Weixiang Cheng

  • Author_Institution
    Dept of Comput., North China Electr. Power Univ., Baoding
  • fYear
    2008
  • fDate
    15-17 Aug. 2008
  • Firstpage
    590
  • Lastpage
    593
  • Abstract
    A gravity-based outliers detection algorithm GODA is presented. Considering that for a data point, both of the density around it and the distance between it and others can influence the outlier´s definition, the algorithm can detect the crytic outliers in the dataset. This paper proposes the definitions and techniques firstly and then introducts the algorithm detailedly. Experiments have been carried out with real data, and the results indicates that not only the new algorithm is of goog extensible ability but also it has higher efficiency of detecting outliers. It points out the outlier´s outlying degree in the dataset as well.
  • Keywords
    data mining; object detection; crytic outliers; datasets; goog extensible ability; gravity-based outliers detection; Business; Cleaning; Detection algorithms; Distance measurement; Electrons; Euclidean distance; Intrusion detection; Multimedia systems; Signal processing algorithms; Stress; gravity; outlier; outlier detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Information Hiding and Multimedia Signal Processing, 2008. IIHMSP '08 International Conference on
  • Conference_Location
    Harbin
  • Print_ISBN
    978-0-7695-3278-3
  • Type

    conf

  • DOI
    10.1109/IIH-MSP.2008.48
  • Filename
    4604126