Applications Of Data Mining Technology In Vocational Eeducation Enrollment Information System

With the development of database technology,popularity of network technology and improvement of computer hardware,the capability of collecting data was improved rapidly , and they have accumulated"massive"data that contains much knowledge,models, rules and so on. In order to obtain the information to guide production and daily life, we put forward the Data Mining Technology. The Data Mining also called knowledge discovering that is the procedure of distilling available information and knowledge from a large number of, incomplete, noise and ambiguous, random data. The extracted information and knowledge is potential useful but the people do not know in advance. The Data Mining had been applied and studied in recent these years,and it has been applied in many domains successfully,such as business,finance and medical treatment.In recent years ,our country emphasized the development of the vocational education,especially the middle vocational education,we are facing challenge in the middle vocational education that we had not encountered before. How to improve competition is an intractable question in the middle vocational schools. In order to analysis and resolve these questions and find the potential information,it can't meet our needs already only to depend on the traditional technology of mathematical analysis and statistics. We want to offer supports to decision for al1 the education commissions and the leaders of the middle vocational school only by means of the Data Mining technology such as cluster rules.Based on the research background of the Data Mining technology and the arithmetic about the Data Mining of cluster rules,this dissertation has finished the following works:l. The research and discussion of the Data Mining about basic knowledge ,the mining objection and finable mode on the base of elementary concept are discussed and concluded detailed. In additional,some regular Data Mining technologies are introduced and analyzed.2.The Data Mining of cluster rules is discussed detailed in the third and fourth chapter. Based on the classic cluster algorithms are concluded and analyzed, and compared the difference of cluster algorithms impersonality, we put forward an improved algorithms of k-means.3. We put forward Vocational Education Enrollment System based on Data Mining in order to meeting realistic needs. In the fifth chapter we introduce the functional components of the system and their roles,and present the application of .net technology and B/S mode in Vocational Education Enrollment System. Additional, we introduce the process of setting up recruiting-students data warehouse in the sixth chapter and basic OLAP operation.4. Introduce applications of Data Mining technology in Vocational Education Enrollment System. In chapter 7 ,we introduce the detailed applications of k-means algorithm in the system,discuss the implement process of Data Mining technology by means of instance. Based on improved algorithm of k-means, we conclude valuable rules and conclusions.