基于软集理论驱动的毕业生推荐系统研究

网络技术的发展为毕业生与企业之间的顺利沟通提供了支持,但大多数招聘或推荐平台依然是各自"表演"的模式,缺乏有效对接.面向毕业生与企业的直接需求、核心需求,在软集理论驱动的基础上,构建一个智能的、支持决策的毕业生推荐平台.该平台允许用户自主设置属性及属性排序,对推荐结果进行优劣排序,使得推荐结果更加客观全面,符合大学生及企业的需求.最后实验表明该方法具有较高的性能.

Research of Graduates Recommendation Platform Driven by Soft Set Theory

Although network technology development serves as an effective link between graduates and enterprises,whereas most recruitments and recommendation platformsare still designed to perform respectively,lacking of effective joints.Catering to the direct needs and core requirementsof graduates and enterprises,an intelligent and decision-supporting graduates recommendation platform is constructed by soft set theory.Recommendation platform allows users to set self-care properties and rank properties,therefore,recommendation results can be sorted in accordance with quality to make them become more objective and comprehensive as well as meeting the needs of college students and enterprises.Finally,experimental results show that the method containshighperformance.