Research of Enterprise Crisis Alert by Data Mining Techniques Based on Rough Set
Facing the drastic market competition and complex environment, the enterprise often meets kinds of crisis, therefore, they need building crisis alert system so as to summarize experience, improve ability of resisting risk and keep themselves develop persistently. This paper gave a classification algorithm by attribute importance (CAAI algorithm). Attributes are reduced by rough set theory, redundant attributes are removed and the core attributes are gained. When building the decision tree through the CAAI algorithm, the current node was chosen from the core attributes of the simplified decision table and decision tree splitting is according to the importance degree of attribute so as to reduce computation and gain relative simple classification rules. An example in cheat crisis alert is given to validate the CAAI algorithm. The results show that the method is effective. The research lays a foundation for further study on enterprise crisis alert system.
cheat crisis enterprise crisis alert algorithm rough set
Wang Hong
School of Economics & Business Administration, Productivity Research Center Heilongjiang University, Harbin 150080, China,Northeast Forestry University Postdoctoral Station, Harbin 150080, China,Heilongjiang Academy of Agriculture Sciences Postdoctoral Work Station Harbin 150086, China
国际会议
成都
英文
60-63
2010-07-09（万方平台首次上网日期，不代表论文的发表时间）