属性约简在高校就业决策分析中的应用

Application of Attribute Reduction Algorithm in Collegiate Employment Decision Analysis

粗糙集理论是一种采用新方式来研究不精确、不确定性知识的数学工具。属性约简的计算是粗糙集理论中的一个重要问题。描述基于粗糙集的属性约简的相关概念,包括核、约简、分类精度;通过分析多种属性约简算法,结合可辨识矩阵和逻辑运算,提出了一种属性约简算法;围绕高校中的管理信息系统,利用该算法抽取与学生就业相关的数据信息,给出了影响学生就业的各条件因素与工作方向之间的依赖关系和约简后的数据表;获取相关规则得出结论,取得了良好的效果。

Rough set theory is a new mathematical tool to research imprecise and uncertain knowledge. Attribute reduction＇s computation takes an important role in this theory, describes the concept of attribute reduction based on the rough set theory, including core, reduction, and classification precision; analyzes many kinds of attribute reduction algorithm; and then comes up with a new attribute reduction algorithm with the help of discernibility matrix and logic operation. It has been proved that in the area of MIS in university, with the employment - related data collected, this algorithm can be applied to achieve the implied relationship between each element and working direction as well as contracted data sheets. Finally it can help gain the correlation rule, draw the conclusion, obtain a good effect.