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随着近几年高校的扩招政策,高职学院的学生人数日益增多,这给就业指导改革工作带来了新的挑战。高职院校迫切需要科学地分析就业指导改革中包含的各项数据,挖掘隐藏的影响就业的各项数据,如学生特征、职业生涯规划、社会岗位需求以及就业信息等。本文在分析了数据挖掘技术在就业指导改革中应用的可行性的基础上,提出了应用数据挖掘聚类分析规则来进行就业指导改革。通过数据挖掘中的聚类分析规则,发现就业指导改革中隐藏的大量数据,为高职就业指导改革提供一些建议,也为学生提供更好的就业指导。
With the enrollment expansion policy of colleges and universities in recent years, the number of students in vocational colleges has been increasing. This has brought new challenges to employment-oriented reform. Vocational colleges urgently need to scientifically analyze the data contained in the employment guidance reform to find out the hidden data that affect employment, such as student characteristics, career planning, social job requirements and employment information. Based on the analysis of the feasibility of applying data mining technology in employment guidance reform, this paper proposes the application of data mining clustering analysis rules to reform employment guidance. Through the cluster analysis rules in data mining, we found a large amount of data hidden in the employment guidance reform, provided some suggestions for the employment guidance reform in higher vocational colleges, and also provided better employment guidance to students.