基于粗糙集的毕业生就业质量评价指标优化

为构建财经类院校毕业生就业质量评价指标体系, 提出一种基于粗糙集理论的就业质量评价指标优化方法。 初步确立毕业生就业质量的 14 个评价指标, 以吉林财经大学 2012 ~2015 年近 4 届毕业生的就业信息为样本数据, 利用定量统计法对各指标权重进行了初步确定, 并对各评价对象进行了初步评价分类。 利用粗糙集论对评价指标进行约简, 剔除不影响评价对象分类的指标, 使指标体系由原来的 14 个指标约简为 6 个指标,并重新确定各指标权重, 最终得到了优化的财经类院校毕业生就业质量评价指标体系。 研究结果表明, 利用优化的指标体系可减少统计与评价的工作量, 该方法为财经类院校毕业生就业质量评价指标体系的构建和优化提供一个新的方向和途径。

Application of Rough Set Theory in Optimization of Evaluation Index of Graduates' Employment Quality

To solve the construction of the evaluation index system of the employment quality of finance and economics college graduates, a new optimization method based on rough set theory for the evaluation index of Employment quality is proposed. Fourteen evaluation indexes are first established, the employment information of Jilin University of finance and economics graduates from 2012 to 2015 is taken as a sample data and the quantitative statistics is used to determine the weight of the indexes preliminary. The evaluation objects are evaluated and classified. The rough set theory is used to simplify the evaluation indexes, eliminate those do not affect the classification. The index system is reduced to 6 indexes from the original 14 indexes, and the weight of each index is re-determined. Finally the optimized evaluation index system of the finance and economics college graduates’employment quality is obtained. Using the optimized index system can reduce the workload of statistics and evaluation. This method provides a new direction and means for the construction and optimization of the evaluation index system of the employment quality of finance and economics college graduates.