Data Mining Technology Applied Research, Analysis Of The Ka Wah College Student Employment

With the effect of college expansion, the number of students at university is increasing so that the managers and the corresponding mode are much more highly required. Therefore, digitized and informationized management is successively adopted, for example, educational administration information, selecting courses and student employment management systems are widely applied at most colleges and universities. With more and more graduates, larger data are accumulating into the database, which are so hidden to difficultly observe some quite important information.Thus, the mining objects in this dissertation are data about past graduates from Canvard College, Beijing Technology and Business University (independent college). The connotative and unknown knowledge is tried to be mined from the graduates' database through data mining technology. Data mining can predict future trend and action, and show the relationship between present data and results, which can help to make knowledge-driving decision in advance. Relevance principle in mining arithmetic is one of important modes in present data mining studies, which emphasizes the relationships between data in different fields, and find out the sufficient dependence of given support and reliability threshold value in different regions. It would bring a mass of candidate frequent predication collection, if multidimensional relevance principle is used and just based on the primal Apriori arithmetic. At present, the inductive method of decision tree is basic to induce data mining based on many rules. Therefore, this dissertation utilized relevance principle and ID3 mining arithmetic. After decision tree produces with the application of decision tree inductive method, the path between the nodes of root and leaf forms the category prediction of corresponding objects. Based on such prediction and effective results, decision tree can clearly show more important field and more direct mine the relationship of graduates'information. Decision tree is used to mine graduates data, in order to search the main factors to affect graduates employment, and efficient approaches to help them hunt jobs, and to improve practicality in instructing graduates employment. Simultaneously, this adapts to the needs of market, changes employment instruction method, cultivation mode and teaching plan, and eventually improves graduates employment.Through mining graduates data, it is found that graduates can usually work in state-owned units, who have done better in integrated achievements, English, thesis and practice. Especially boy party member of the same more possibly choose to further study.The results of data mining will applied to students' management and teaching so as to focus on training students' English, speciality and practice, better adapt the social needs and cultivate eligible graduates with ability.