基于标签聚类和协同过滤算法的就业推荐系统设计  

Design of Employment Recommendation System Based on Label Clustering and Collaborative Filtering Algorithm

作　　者：薛亮 冯尊磊 凌兴宏 龚兰兰 何伟亚 XUE Liang;FENG Zunlei;LING Xinghong;GONG Lanlan;HE Weiya(College of Computer and Information,Hohai University,Nanjing 211100,China;Computing Science and Artifical Intelligence College,Suzhou City University,Suzhou 215104,China;College of Computer Science and Technology,Zhejiang University,Hangzhou 310027,China)

机构地区：[1]河海大学计算机与信息学院,江苏南京211100 [2]苏州城市学院计算机科学与人工智能学院,江苏苏州215104 [3]浙江大学计算机科学与技术学院,浙江杭州310027

出　　处：《微型电脑应用》2024年第1期1-4,共4页Microcomputer Applications

基　　金：国家自然科学基金青年科学基金(62003218);教育部高等教育司产学合作协同育人项目(201902295009)。

摘　　要：随着毕业生就业压力的增大,国家和社会持续发力,国家出台多项就业支持政策,社会上的企业招聘也日渐增多。在此背景下,设计了一种个性化的就业推荐系统。系统基于Web应用,主要功能包括用户注册和登录、用户选择感兴趣领域、职位推荐、职位收藏及查看职位详细内容。其中注册和登录功能的实现借用了Django内置的Auth模块;数据库用的是Django框架下的Sqlite3;职位推荐是基于用户信息的协同过滤算法实现的,并且用标签聚类的方式解决了冷启动问题。仿真结果表明,用户可以注册之后登录并选择自己感兴趣的领域,然后就可以查看系统推荐的职位,具有较好的效果。As the employment pressure of graduates gradually increases,the state and society continue to make efforts.The state has issued a number of employment support policies,the social enterprise recruitment is also increasing.Under this background,this paper designs a personalized employment recommendation system.The system is based on the Web application.The main functions include user registration and login,user selection of interested fields,job recommendation,job collection and view the detailed job content.The registration and login functions are implemented using Django's built-in Auth module.The database uses Sqlite3 in the Django framework.Job recommendation is realized by collaborative filtering algorithm based on user information and solved the problem of cold start by label clustering.The simulation results show that users can log in after registration and select the field they are interested,and then they can view the positions recommended by the system,which has a good effect.

关 键 词：就业推荐 协同过滤 仿真 系统设计 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]