Data Mining Technology In The Employment Of Graduates Work In Applied Research

In recent years, the employment problems of university graduates in our country appeared unceasingly, the reason is not only the economy reform, enlarging the scale of enrollment, the lack of education resource, and the imperfect employment model, but also the unsuited model of higher education. It is urgent that we deepens the higher education reform, and ameliorates the education model of university. The universities and colleges needs to face the society and train the application students.In this article we attempts to discover the associative relations between the education attributes and the employment attributes of graduates and find the type of application person which the society needs through the data mining technology.Association rules mining is one of important matters of data mining. Mining data between people characters and their actions is an important aspect for multidimensional association rules. For example, association trend between students'nature information and their behavior. But many general mining tools have not paid much attention to these aspects. In this paper, we mainly researched multidimensional association rules mining, and propose a more efficient means which is based on the original algorithm in multidimensional association rules mining. and using the means, we design a system to analyze the rules of undergraduate employment.The system mainly includes two parts: the manipulation of database (accessing,querying and updating the database) and mining data in the background. It is based on Microsoft Access 2003 database and the core algorithm of data mining is improved Apriori algorithm. After analyzing the data of undergraduate employment, the system can give us some meaningful rules, which will show the relationship between the students behaved in university and obtained employment information after graduated and can help authority concerned make better decision to assist the students to find a job.