• DocumentCode
    2054073
  • Title

    VOD: A Novel Outlier Detection Algorithm Based on Voronoi Diagram

  • Author

    Qin, Wen ; Qu, Jilin

  • Author_Institution
    Sch. of Comput. & Inf. Eng., Shandong Univ. of Finance, Jinan, China
  • Volume
    2
  • fYear
    2010
  • fDate
    14-15 Aug. 2010
  • Firstpage
    40
  • Lastpage
    42
  • Abstract
    Outlier mining is an important branch of data mining and has attracted much attention recently. The density-based method LOF is widely used in application. However, the complexity of the method is quadratic to size of the dataset, and it is very sensitive to its parameters MinPts. In this paper, we propose a new outlier detection method based on Voronoi diagram, called Voronoi based Outlier Detection (VOD), to provide highly-accurate outlier detection and reduces the time complexity from O(n2) to O(nlogn).
  • Keywords
    computational complexity; computational geometry; data mining; MinPts parameters; Voronoi diagram; data mining; density based method; outlier detection algorithm; Approximation algorithms; Clustering algorithms; Complexity theory; Data mining; Estimation; Information systems; Nearest neighbor searches; Voronoi diagram; algorithm; data mining; outlier detection;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering (ICIE), 2010 WASE International Conference on
  • Conference_Location
    Beidaihe, Hebei
  • Print_ISBN
    978-1-4244-7506-3
  • Electronic_ISBN
    978-1-4244-7507-0
  • Type

    conf

  • DOI
    10.1109/ICIE.2010.105
  • Filename
    5571223
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2054073