计算机科学 ›› 2015, Vol. 42 ›› Issue (Z11): 1-4.
• 智能计算 • 下一篇
乔非,葛彦昊
QIAO Fei and GE Yan-hao
摘要： 在高校就业信息化建设中,对进入高校招聘毕业生的企业客户进行等级分类和预测能够有效帮助高校管理者评估与该企业的合作效用,推动大学生就业信息化服务向更具针对性的个性化推荐方向发展。目前该问题的解决方案大多基于从业人员的主观经验判断,缺乏完善的定量分析模型。抽取某高校教育管理信息系统中与进校招聘企业客户相关的数据样本,并借助BP神经网络模型搭建有效的数据分析模型,使用训练样本数据训练模型从而确定分析模型中各节点参数,将训练后的分析模型用于预测测试样本集得到最终的性能指标,最后将该模型的分类性能与当前同类问题的其他解决方案进行比较。对比结果显示,基于BP神经网络模型的分类方式在预测准确度和精度方面明显优于其他现有模型。该研究成果能够在信息化平台中为该问题提供高效的解决方案,帮助高校就业工作管理者及服务人员依靠该模型对进校招聘企业做出快速精准的客户等级预测,为高校就业服务工作决策提供支持。
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