基于改进神经网络的高校就业信息推荐系统  

University Employment Information Recommendation System Based on Improved Neural Network

作　　者：刘雪梅 胡博 吴慧玲[1] LIU Xuemei;HU Bo;WU Huiling(Henan University of Animal Husbandry and Economy,Zhengzhou Henan 450046,China)

机构地区：[1]河南牧业经济学院,河南郑州450046

出　　处：《信息与电脑》2022年第9期80-82,共3页Information & Computer

摘　　要：为提高毕业生推荐就业信息的吻合度和命中率,笔者提出基于改进神经网络的高校就业信息推荐系统。硬件部分设计了三层架构,分别为数据层、逻辑层、表示层;软件部分通过计算大学生就业方向信息的相似度,将相似度高的信息聚类为同一类别数据,利用改进神经网络训练数据,并输出同一就业方向的推荐信息。实验结果表明,设计系统提高了推荐结果的吻合度和命中率,具有较小的推荐排名指数,推荐信息与毕业生的个性化需求更吻合,充分保证了推荐结果的准确度。In order to improve the coincidence and hit rate of graduates’recommended employment information,a recommendation system of university employment information based on improved neural network is proposed.Part of the hardware is designed with three layers of architecture,namely data layer,logic layer and presentation layer.Part of the software calculates the similarity of college students’employment direction information,clusters the information with high similarity into the same category data,trains the data by using the improved neural network,and outputs the recommendation information of the same employment direction.The experimental results show that the design system improves the coincidence and hit rate of recommendation results,has a small recommendation ranking index,and the recommendation information is more consistent with the individual needs of graduates,which fully ensures the accuracy of recommendation results.

关 键 词：改进神经网络 就业信息 推荐系统 准确度 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]