• DocumentCode
    1844765
  • Title

    An enterprise crisis predicting system based on outlier data mining

  • Author

    Song, Yan

  • Author_Institution
    Sch. of Econ. & Manage., Harbin Eng. Univ., China
  • Volume
    2
  • fYear
    2005
  • fDate
    13-15 June 2005
  • Firstpage
    1035
  • Abstract
    Many factors in an enterprise are playing important roles in intense commercial competitions. Some are positive and some are negative. If dealing with these factors correctly, potential crisis will be found to avoid defeats, even bankrupt. Designing a crisis predicting system is necessary. An excellent predicting can not only predict expecting crisis and take controlling measures, but also can provide enough preparation and plan to deal with crisis smoothly. The factors are the basis data to be analyzed to support such a system and maybe they are quantitative or qualitative. In order to solve such problems as half-structured and non-structured data analysis in enterprise crisis predicting system, a predicting system based on outlier data mining is put forward. The system organization, frame construction, function and working principles are illustrated. And the working process is showed by an example of cheat predicting. The experimental results show that this method is efficient and it has wide utilization in predicting fields.
  • Keywords
    corporate modelling; data analysis; data mining; pattern classification; pattern clustering; commercial competitions; data analysis; enterprise crisis predicting system; outlier data mining; Clustering algorithms; Crisis management; Data analysis; Data engineering; Data mining; Data models; Economic forecasting; Engineering management; Fault tolerance; Predictive models;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Services Systems and Services Management, 2005. Proceedings of ICSSSM '05. 2005 International Conference on
  • Print_ISBN
    0-7803-8971-9
  • Type

    conf

  • DOI
    10.1109/ICSSSM.2005.1500150
  • Filename
    1500150