Design And Implementation Of E-recruiting Systemfor University Graduates Majoring In Software Engineering

With the successive growth of a number of university graduates, the employment of university graduates is getting the attention of more and more social concern. In the past few years, information technology developed rapidly, and because of informative, less geographical restrictions and the great advantage of low recruitment costs, E-recruitment gradually becomes the common choice of job seekers and enterprises. However, job seekers and enterprises need to spend a lot of time and effort to choose a proper job or a talent that can meet requirements and satisfy themselves from the massive recruitment information. On the other hand, the traditional keyword-based information retrieving technologies can not satisfy the demands of the customers of E-recruiting system. Therefore, it is necessary to study the recommendation technologies and its practical applications in E-recruitment, and develop an E-recruiting system which can provide personalized recommendation service.Based on the development project of E-recruiting system conducted by a company, and by making an analysis on the study of the current recruiting systems,the characteristics of university students and the enterprises special requirements on them, this thesis realized the E-recruiting system for university graduates majoring in software, and put forward a job recommendation algorithm as well. The main work contents are as follows:Firstly, study on the existing text similarity computation theory. By using Vector Space Model, this thesis turns the matching problem between the resume and the recruitment information into the issue of vector similarity, and makes reasonable quantitative rules.Secondly, combines with the characteristics of the E-recruitment, this thesis introduces the feature weight and influence factor of time into similarity computation. The algorithm makes use of a variety of similarity computation methods to guarantee the accuracy and rationality of similarity computation. Meanwhile, based on the recommendation results, the similarity computation method between job seekers and enterprises is proposed by data modeling and analyzing the recruitment history information, so as to optimize the recommendation results and then the recommendation accuracy was enhanced.Finally, based on the open source software, including Spring, i Batis and j Query framework, combining with job recommendation algorithm designed in this thesis, we realized the E-recruiting system for university graduates who majoring in software. Aiming at the specific groups – the university graduates majoring in software, we design and implement a talent assessment system, and introduce the talent assessment service into recruitment process. Furthermore, the function of interview appointment increases the interaction between job seekers and enterprises and meanwhile reduces the workload of the customers of E-recruiting system and improves the efficiency of recruitment. After a comprehensive test, this system not only makes the work flow more convenient and efficient but also makes the recruitment becomes easy and simple. In addition, the system offers a convenient and strong practicability platform for both enterprises and job seekers, which enables the both sides to share as much information as possible.