Design And Implementation Of Intern Recruitment System Based On A Content Recommendation

It is a competitive society today, and the nature of competition is the talent competition. It has become the consensus of the community that who has the talent needed, and it will come in an invincible position in the competition.On the one hand, students practice become increasingly important as the number of college graduates increased year by year and students' employment increasing competitive pressure. On the other hand, companies need to recruit high-quality personnel for training to improve the efficiency and promote corporate team younger.Students and recruiters both need a smooth recruitment platform for exchange and communication.But the existing information retrieval based on keyword function has become increasingly difficult to meet the needs of users.Therefore we need to study recommendation technology and its application in the network recruitment to develop a network recruitment system with personalized recommendation service.This is a research paper,which is based on the analysis of research on the basis of the existing recruitment website, especially on the features of the college students and recruiters, and put forward a new a job recommendation algorithm based on recruiting content. The system mainly has the following three aspects :First, introduces the basic theory of the similarity calculation and application of space vector model. Put matching problem of the resumes of students and recruiters information into the the vector similarity problem, and develop a reasonable quantitative rules for other features. Introduce clustering method, and use K-means algorithm to cluster enterprises, to ensure that the K-means algorithm convergence and solve the problem of K values.Second, Design and implement a position recommendation algorithm based on the job description, which has 5 steps: Keyword filtering, quantization rule, similarity computing, enterprise clustering and sorting Top NThird, this design with role-based content recommendation algorithm, three-tier architecture and Struts2.0 as the basic framework, using DAO(Data Access Object) for data storage and retrieval, and using database technology to develop, design and implement intern recruitment system.The system is divided into four modules: Students module, recruiters module, the administrator module and positions recommendation module, which can realize the students to find an internship, companies to recruit talent.This intern recruitment system is simple and safety, and provides a convenient and fast communications platform for recruiters and interns.