一种基于在校历史信息的就业推荐算法  

An Employment Recommendation Algorithm Based on Historical Information of College Students

作　　者：尹传城 王洪国[1,2] 丁艳辉[1,2] 

机构地区：[1]山东师范大学信息科学与工程学院,济南250014 [2]山东省分布式计算机软件新技术重点实验室,济南250014

出　　处：《计算机与数字工程》2015年第10期1742-1745,1750,共5页Computer & Digital Engineering

基　　金：国家自然科学基金青年项目(编号:61303007);山东省优秀中青年科学家科研奖励基金(编号:BS2013DX044)资助

摘　　要：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。由于相关数据获取困难,导致传统的就业推荐方法缺少对高校毕业生在校历史信息的综合考虑和利用。论文提出一种基于高校毕业生在校历史信息的就业推荐算法,充分利用BP神经网络和不同性质的单位招收毕业生的偏好特点,改进传统的应届毕业生与往届毕业生之间的相似度计算方法。通过该方法,将在校历史信息相似的往届毕业生的求职去向,推荐给应届毕业生,为其提供参考和指导。通过对历史数据进行评测,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。The number of college graduates has increased in recent years.The problem of college graduates＇employment has attracted more and more attention of the government,the school and students.The traditional methods of job recommendation usually lack of considering and utilizing the historical information of these graduates.In the paper,a recommendation algorithm is propsed,which based on the historical information of the college graduates in school.The algorithm,makes full use of BP nrural network and the preference of different enterprises and institutions when they recruit graduates,improve the traditional methods of similarity calculation.After similarity calculation between the new graduates and the perivious graduates,the similar perivious graduates and their jobs are recommended to the current user.Experimental results show that the algorithm can effectively provide a guidance for the new graduate.

关 键 词：就业推荐 在校历史信息 相似度 BP神经网络 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]