Zeng Qiaozhi, Zhang Hong
With the rapid development of internet technology, job search websites have become an important part of the modern recruitment market. This paper introduces a job search website called Cloud Job Reach, which is based on the Spring Cloud microservice architecture and integrates instant messaging, video interviews, personalized recommendations, and AI assistants. The goal is to improve the efficiency of interaction between job seekers and recruiters and enhance the precision of matching. The paper focuses on the design of personalized job recommendations based on the user collaborative filtering recommendation algorithm (UBCF), which recommends jobs by analyzing the similarity of user behavior. The system is developed using Java, with MySQL and Redis as the database, and the front-end uses the Vue framework. The system demonstrates good extensibility and stability through the use of Spring Cloud Alibaba's Nacos and Spring Gateway. Cloud Job Reach also integrates AI technology to improve the website's intelligence level. The paper describes the system design, development environment, technical architecture, database design, function implementation, and system testing in detail, verifying its effectiveness in terms of functionality, performance, and user experience.
Microservice Architecture; Job Search Website; Instant Messaging; Video Interviews; Collaborative Filtering Recommendation Algorithm; Artificial Intelligence Assistant.