Analysis,Optimization And Application On The Algorithms Of Mining Association Rules

At present , the enrollment of most universities has all already been up to scale of as many as ten thousand even more than one hundred of thousand; teacher's number has been above a thousand too. Various kinds of systems and databases are using in university. for example, roll management, achievement management and so on. A large amount of data has been already accumulated. The administrative staff can only obtain superficial information by simple statistics or sequencing functions, because of lacking the information consciousness and technology, the information hidden in the large amount of data has never got application. Many universities are considering the following question: how to utilize the data again, how to translate the existing management data into the knowledge suitable for using, how to improve management decision-making in school and improve management level and teaching quality. Data mining can solve these problems and use the function of the information system effectively.Data mining is the process of extracting, identifying and discovering potentially valid, useful, previously unknown, and ultimately understandable knowledge(rules or patterns). Data Mining technology can identify different data models from the existing data , so it can help the user understand the existing information and predict the future development of the business based on the present condition . The data mining of association rules is an essential research aspect in the data mining fields . Association rules reflect the inner relationship of data. Discovering these associations is beneficial to the correct and appropriate decision made by decision-makers.The algorithm related to association rules fall into two categories according to the needs of producing candidate itemsets or not, mainly Frequent-Pattern tree and Apriori-like approach. The main difference is that Frequent-Pattern tree does not produce candidate itemsets ; it compresses the database within the structure of Frequent-Pattern tree to prevent time-consuming database from search work. The latter is the approach with needs to need to produce candidate itemsets.The thesis introduces the principles of data mining and the methods of association rules in detail. Stem from these theory ,the paper analyses the classic association rule algorithm——Apriori from theoretical and practical perspective. To make up for its deficiency ,two new algorithms have been proposed .The concrete conditions of present educational administration management of the foundation of this text, apply the method of association rule data mining to recruit suitable students. By applying the method to educational administration management we obtain many valuable knowledge which are helpful for college education.