贝叶斯网络在就业风险评估中的应用  

Application of Bayesian networks in employment risk estimation

作　　者：任雪利[1] 

机构地区：[1]曲靖师范学院计算机科学与工程学院,云南曲靖655011

出　　处：《计算机时代》2013年第3期35-36,共2页Computer Era

基　　金：云南省教育厅基金项目(2011Y010)

摘　　要：高校扩招带来了大学生数量大幅度增长,毕业生就业问题已经成为高校管理中的重大问题。在对近年来就业风险评估研究的基础上,提出了用贝叶斯网络来解决就业风险评估和预测的问题,为了降低先验概率的主观性,引入了模糊综合评判的方法。以某校前几年的就业信息来训练就业风险评估的贝叶斯网络模型,实验结果表明,专业成绩和实践水平在影响就业的主观因素中占有重要的地位,为今后的教学及就业提供了有益的指导。With the substantial increase of college students, the employment of students becomes a major problem for colleges and universities. A solution to solve risk estimation is proposed in this paper by using Bayesian network and fuzzy estimation to estimate the subjection of prior probability. Bayesian network model to assess employment risk is trained using the employment database of a school a few years ago. The experimental results show that the professional achievements and practical level have played a very important role in the subjective factors to affect employment. It can be a useful guidance for future education and employment.

关 键 词：就业 风险评估 贝叶斯网络 模糊综合评判 

分 类 号：TP393.092[自动化与计算机技术—计算机应用技术]