基于协同过滤算法实现高校个性化就业推荐系统研究

Research on Personalized Employment Recommendation System in Colleges Based on Collaborative Filtering Algorithms

高校毕业生就业形势严峻、竞争异常激烈。'就业难'源于毕业生对于企业需求认识不足和对自我的认知不足,所以很多时候只能找一个专业不对口又不感兴趣的工作,而企业又出现的'招人难'的现象,又造成了毕业生和企业双方的损耗。协同过滤算法的个性化就业推荐系统,能够通过挖掘学生的兴趣爱好、职业导向等多重信息,从而生成学生就业兴趣模型,同时结合以往毕业生就业数据,为毕业生提供适合自身的就业推荐导向。本文重点介绍了基于协同过滤算法的就业推荐概念及基于协同过滤算法实现高校个性化就业推荐系统是如何开发设计的。

The employment situation of college graduates is severe and the competition is fierce.'difficult employment'is due to the lack of awareness of the needs of enterprises and self-awareness of graduates,so many times they can only find a job that is not suitable for your major and not interesting,and the phenomenon of'difficult recruitment'appears in enterprises,which results in the loss of both graduates and enterprises.Through the personalized employment recommendation system based on collaborative filtering algorithm,the model of students’interest in employment can be generated by mining multiple information such as students’interests,career orientation and so on.At the same time,combined with previous graduate employment data,it can provide graduates with suitable employment recommendation guidance.This paper focuses on the concept of employment recommendation based on collaborative filtering algorithm and how to develop and design the personalized employment recommendation system based on collaborative filtering algorithm.