摘要
对于高校就业管理信息系统中积累的大量数据,运用数据挖掘算法中的决策树方法挖掘出潜在的有用的信息,为高校开展就业工作提供决策支持。根据就业数据的特点,采用C4.5决策树算法,对就业数据进行预处理,选取决策属性,实现挖掘算法并抽取规则知识,由规则知识指出哪些决策属性决定了就业单位的类别。挖掘结果表明,该算法能够正确将就业数据分类,并得到若干有价值的结论,供决策分析。
Mines useful and unobvious information from the vast data stored in employment management information system by data mining. Uses C4.5 decision-tree algorithm, preprocesses the data and chooses the decision attributes first, then draws the rules, which shows what attributes determine the classification of employment. The results of data mining indicate that the algorithm can classify the employment data properly and get some valuable information for decision-making.
出处
《现代计算机》
2008年第3期90-92,共3页
Modern Computer
关键词
数据挖掘
就业
管理信息系统
决策树
C4.5
Data Mining
Employment
Management Information System
Decision-Tree
C4.5
