基于深度学习的大学生求职能力与岗位匹配模型构建

Construction of College Students’ Job-Seeking Ability and Job Matching Model Based on Deep Learning

摘要: 大学生就业关系着高校毕业生的稳定，也与国家经济快速发展密不可分，但疫情影响、每年持续上涨的高校毕业生人数、大学生社会经验不足、能力缺乏等都对大学生就业产生不利影响，部分学生至今未解决就业问题。为解决大学生就业难问题，构建大学生求职能力与岗位匹配平台，依托模型预测学生自身的综合能力，进而选择自己感兴趣或者擅长的领域，之后和岗位能力需求进行对比分析，并借助于深度学习DISC算法对岗位能力偏差进行深入的剖析研究，深入了解企业文化，最后结合偏差结果在平台上匹配到相对适合的岗位，进行线上模拟。系统选择使用微信小程序框架、Servlet技术、MYSQL数据库等研发人员常用的系统开发工具，其界面简洁直观，功能丰富，性能出色。

Abstract: The employment of college students is related to the stability of college graduates, also is inseparable with the rapid development of the national economy, but the impact of the epidemic, the number of college graduates continues to rise every year, college students lack of social experience, lack of ability to have a negative impact on the employment of college students, some students have not solved the employment problem. In order to solve the difficult problem of college students’ employment, build a platform to match college students’ job-hunting ability with their positions, rely on the model to predict students’ comprehensive ability, and then choose the fields they are interested in or good at, and then compare them with the job requirements. The DISC algorithm of deep learning is used to analyze the deviation of job ability, so as to deeply understand the enterprise culture. Finally, the deviation results are combined to match the relatively suitable positions on the platform for online simulation. The system uses wechat small program framework, Servlet technology, MYSQL database and other mainstream development tools and technology interface is simple and friendly, good performance.