基于兴趣敏感度的高校毕业生就业推荐算法

摘要

The number of college graduates has increased in recent years.The problem of college graduates' employment has attracted more and more attention of scholars and the society.The traditional methods of job recommendtion usually lack of considering and utilizing the historical information of graduates.In this paper, a recommendation algorithm is proposed, which is based on the sensitivity of interest.firstly, the algorithm makes full use of employment data and improves PersonalRank method to calculate the sensitivity of interrest of different enterprises when they recruit graduates.Then, improves similarity calculation method between the graduates and previous graduates.Finally, the job of the similar previous students are recommended to the current user by combineing with the credibility of enterprises.Experimental results show that the algorithm can provide a guidance for the new graduates effectively.%近几年,随着高校毕业生数量的逐年增长,高校毕业生的就业问题已引起社会及相关学者的广泛关注.高校毕业生在校历史信息等数据获取困难,导致传统的就业推荐方法缺少对相关数据的综合考虑和利用.论文提出一种基于兴趣敏感度的就业推荐算法.首先,在充分利用高校毕业生与往届就业数据的基础上,提出Sensitive-PersonalRank算法,计算不同企业在历史招聘数据中体现出的对应届毕业生的兴趣敏感度;然后结合兴趣敏感度改进应届毕业生与往届毕业生之间的相似度计算方法;最后,结合企业信任度,将相似的往届毕业生的就业去向推荐给应届毕业生,为其就业提供参考和指导.通过对山东师范大学提供的历史数据进行评测,实验结果表明,该方法可以有效地为应届毕业生提供就业指导和参考.