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
Link To Document :
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