The Design And Implement Of Graduate Occupation Recommending System

In recent years, because of the continuously growing number of the college graduates and the adverse impact on China's economy caused by the global financial tsunami,the college graduates faced an increasingly tough job market. However, at present, the graduates-employment service of all the universities in China cannot fully provide each graduate with proper and effective employment guidance and job recommending. Besides, what universities'employment networks have is only recruitment information releasing function, but not information recommending function. The design and development of "the employment recommending system for the college graduates" can just fill the gap. By using this system, the college graduates can get a scientific and reliable employment recommendation according to their individual circumstances. With the recommendation, the graduates can make a wiser choice for their career.As the existing network platform in the employment recommending process has flaws, we have designed "the employment recommending system for the college graduates", which has taken the features of graduates'seeking jobs as well as campus recruitment into consideration. In the system design process, we compare the basic features of fresh and previous graduates and get the similarity of these two groups of graduates by using the empirical formula and Simrank algorithm respectively. Then, based on the result, we obtain the similarity of the fresh graduates and enterprises in further cluster analysis. Finally, we get all enterprises' recommendation-ranking weight by combining the similarity (of the fresh graduates and enterprises) with the enterprise's "Job Index" which is obtained by PageRank algorithm. Thus, several top enterprises in our rankings will be recommended to the graduates.Though this article has applied two different algorithms for calculating the similarity between graduates, we choose the empirical formula in the final system according to the result from the comparative testing experiment in Chapter V of this article. We can conclude from the testing experiment result that the final system not only meet the original intention in function, which can effectively offer scientific and reasonable employment recommendation to the graduates, but also help those who lack job objectives to set one and enhance the success rate in seeking a job, which to some extent means reducing the cost in job seeking. Compared with the simple information releasing function of the present employment network, the employment recommendation function in our system has a higher practical value.