基于粗糙集的大学生学习与就业关系分析

Relationship Analysis of Undergraduate Students' School Records versus Employment Based on Rough Set

随着社会经济的高速发展,人才需求的多元化,国内的教育事业进入了大众化的新时期,毕业生数量逐年增加,导致了高校毕业生就业形势越来越严峻,学生就业难已成为当前社会的热点问题。大学生在校学习成绩作为学生智力、学习态度等因素的直观结果,较为准确地反映了学生的整体水平,也与学生就业有着紧密的联系。为了帮助高校学生合理利用在校学习时间,有导向的进行学习,采集了已毕业计算机科学与技术专业学生在校学习成绩和就业信息数据,利用邻域粗糙集的基本理论,对预处理后的学生成绩就业信息表中的课程属性进行约简,并对得出的属性约简子集进行了详细分析,将学习与就业之间的比较准确的内在联系提供给在校学生,帮助学生找到心仪合适的工作。

With the rapid development of social economy, the diversification of demand for talent, the domestic education has entered a new era of popularization. The number of graduates has increased year by year, resulting in increasingly severe employment situation of college graduates, therefore the student employment has become a hot issue of society. As an intuitive result of students ＇ intelligence, learning attitude and other factors, students＇ academic performance more accurately reflects the overall level of the students, and also has a close relationship with employment. In order to help college students make reasonable use of their time for guiding learning, the achievement and employment data of the graduate majored in computer science and technology have been collected with basic theory of neigh- borhood rough set to reduce the grade attribute of student learning-employment table that has been preprocessed. Analysis on attribute reduction subset obtained has been carried out which could provide a more accurately intrinsic link between learning and employment to help undergraduate students find a favorite job.