The Analysis And Design Of The Dynamic Recruitment And Decision Analysis System For College Students

The current recruitment fair, due to its poor simultaneity and collaboration, cannot meet the needs of its participants. Since their inability to obtain in advance detailed information about the employers and college graduates and the usually untimely post-fair feedback, the busy fair has poor efficiency. It is time and energy-consuming for both employers and job hunters and at the same time places a heavy burden of labor on the fair.By studying the means and methods of recruitment, utilizing the advantage resources of Beijing College Graduates Career Guidance Center, and aiming at new demands of employers and college graduates, the paper has proposed a new mode of online recruitment plus site recruitment in an effort to improve the results of college graduates’job hunting, employers’recruitment and the Guidance Center’s performance. In this paper, the author analyzes the demands and functions with the UML’s case diagrams and sequence diagrams, examines the system structure and data flow with traditional methods, and establishes the data storage model with the entity-relationship (ER) diagrams for the design of the dynamic job recruitment and decision analysis system. This system collects information from the recruitment fair and offers employment statistics, analysis and releases, thus providing the direction for schools to improve their students’skill training, career guidance and policy advisory services and improving the quality and number of employers and job hunting students as well as the efficiency and quality of recruiters. 1. Personal identity is validated and information is collected at the recruitment fairNo recruitment fair till now has ever validated personal identities of the participants, and it is introduced into this project as an attempt. In this project, the Guidance Center, schools, and employers are equipped with the second-generation ID card scanner to dynamically validate and collect participants’personal information. By means of this system, schools can obtain and analyze dynamic fair-related statistics, including the number of their students, employers’interviews, and the posts students have been interviewed for.2. WEB2.0technology is used to improve the results of job hunting.Before the recruitment fair is held, its publication is released. The college graduates submit their resumes, and the employers screen them. Using the dynamic data collected at the fair, the system match the graduates and the employers so that the employers can know if students they want have come and send invitation messages to them. The information match before the interview, coupled with the SMS and website support, will improve the efficiency of employment and at the same time reduce paper waste.3. The SPSS’s data mining is used to define the analysis model.Since both schools and the Guidance center update their system frequently, the definable data integration technology is used to assist data collection. By introducing data collection based on the search engine technology and deep data integration, the system analyzes data when idle, automatically sorts it out, files it into the database, and then distributes it to schools and the Guidance Center. Without increasing their workload, it provides the complete original data for their statistics, analysis and decision-making.