基于协同过滤算法的就业推荐系统设计与实现  

Design and Implementation of Employment Recommendation System Based on Collaborative Filtering Algorithm

作　　者：田圻 代齐润 TIAN Qi;DAI Qi-run(School of Intelligent Engineering,Hubei Industrial Polytechnic,Shiyan 442000,China)

机构地区：[1]湖北工业职业技术学院智能工程学院,湖北十堰442000

出　　处：《湖北工业职业技术学院学报》2025年第1期75-79,共5页Journal of Hubei Industrial Polytechnic

基　　金：湖北工业职业技术学院科研项目“基于协同过滤算法的就业推荐系统设计与实现”(2024KQ04)。

摘　　要：面对日益激烈的就业市场和信息过载问题,精准的就业推荐系统对于提高大学生就业率和企业招聘效率至关重要。为此,研究并提出了一种基于协同过滤算法的智能匹配方案,旨在连接大学生求职需求与公司招聘岗位。该系统融合了用户-项目协同过滤和内容过滤策略,以提升推荐的准确性和多样性。采用Spring Boot和Vue 3构建前后端分离架构,确保实时数据交互与处理的高效性,并重视用户隐私保护与数据安全。实验结果表明,本系统有效提升了求职体验和招聘效率。未来工作将聚焦于优化算法、丰富功能及探索个性化服务。Facing the increasingly fierce job market and the problem of information overload,an accurate job recommendation system is crucial to improve the employment rate of college students and the efficiency of corporate recruitment.An intelligent matching scheme based on collaborative filtering algorithms is studied and proposed in this paper,aiming at connecting college students’job-seeking needs with companies’recruiting positions.The system incorporates user-item collaborative filtering and content filtering strategies to enhance the accuracy and diversity of recommendations.Spring Boot and Vue 3 are used to construct the front-end and back-end separation architecture to ensure the efficiency of real-time data interaction and processing,and to emphasize user privacy protection and data security.Experimental results show that this system effectively improves the job search experience and recruitment efficiency.Future work will focus on optimizing algorithms,enriching functions and exploring personalized services.

关 键 词：推荐算法 协同过滤 就业推荐系统 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]