基于个性化推荐算法的全方位入职服务平台设计

Design of an All-round Employment Service Platform Based on Personalized Recommendation Algorithm

求职服务工作是各院校和社会服务的一项重要工作,解决招聘工作数量和质量上的问题是该平台的关键,同时,服务应聘者生活和职业需求,让应聘者进行高效匹配适合学生自己的职位。该软件基于java技术以及部分深度学习进行开发,采集各种职业信息、大量工种求职心理信息、求职经验信息、衣食住行信息等进行数据整合,数据清晰,通过机器学习能够识别不同性格和不同心理的人适合的职业。该平台的核心是职位推荐算法,爬取算法,相似度算法算法,实现职位的最大效率化推荐,让用户仅通过该软件就可获得丰富的求职及相关资源信息。

Providing students with employment services is a key task of many colleges with afocus on the quantity as well as the quality of recruitment.In the meantime,such employment services can meet various needs of applicants either in life or during their careers,enabling them to efficiently find suitable positions.Based on Java programming and deep learning,this application is developed to help with job hunting by collecting all kinds of information such as job titles,pay information,tips on overcoming bar⁃riers to employment and experiences from other job seekers.What’s more,through machine learning,the app is able to pick up the most suitable occupations for people with different personalities.With the help of job recommendation algorithms,crawler technolo⁃gy,big data andsimilarity algorithm,the platform aims to provide all job hunters with a variety of careerinformation and other re⁃sources so as to help them get suitable jobs as soon as possible.