• DocumentCode
    2302834
  • Title

    Research of anomaly detection of laboring statistical data based on DBSCAN cluster algorithm

  • Author

    Li Peng-lin ; Ruan Jin-jing

  • Author_Institution
    Inst. of Comput. Network Applic., Zhejiang Univ. of Technol., Hangzhou, China
  • fYear
    2012
  • fDate
    29-31 Dec. 2012
  • Firstpage
    1398
  • Lastpage
    1400
  • Abstract
    Traditional data analysis becomes harder and harder to satisfy the need of the socioeconomic development in the field of statistics. Basing on principles and method of data mining, this paper applies the DBSCAN algorithm to anomaly detection of laboring statistical data and determines the parameters according to the trait of laboring statistical data. Then detect abnormal data in statistics data by clustering and provide suggestions of the random inspection.
  • Keywords
    data analysis; data mining; government data processing; pattern clustering; statistical analysis; DBSCAN cluster algorithm; anomaly data detection; data analysis; data mining method; laboring statistical data; random inspection; socioeconomic development; Anomaly detection; DBSCAN cluster algorithm; Laboring statistical data;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science and Network Technology (ICCSNT), 2012 2nd International Conference on
  • Conference_Location
    Changchun
  • Print_ISBN
    978-1-4673-2963-7
  • Type

    conf

  • DOI
    10.1109/ICCSNT.2012.6526181
  • Filename
    6526181