Frequent Pattern Mining Based On Fp-tree Algorithm Elective System Design And Implementation

Data warehouse and data mining are two of the most active branches of database studying, developing and application, and also the key factors of DSS. Data warehouse is a decision supporting, subject-oriented, integrated, stable and time-dependent collection from database and data of data; data mining is to analyze data and acquire knowledge warehouse using the method of artificial intelligence binding of them will provide a strong basis of decision analyzing for enterprises related departments.With the research of theory in data warehouse and the data mining studying, a new approach has been proposed in order to reflect the special requests of the course enrolment. As the system and mode reformation in universities, the course enrolment now becomes one of the most important issues in college affairs. The modern educational administration needs the support from modern information management systems. Most of the previous student management systems are the On-Line Transaction Processing (OLTP) systems that have no ability of synthetic analysis, decision support, and the utilization of hidden knowledge from vast history information. Analysis of teaching management is an important way to teaching evaluation. It is necessary to guarantee the quality of teaching and improve the stuff of students analyzing the data made in processes of tests and teaching analysis. And then supporting the teaching with the results by studying data warehouse theory and data mining technology, combined the characteristics of test analysis system.The system include two major parts , which is the student's course enrolment system and the data analysis system. The paper introduces thedata of choosing courses analysis system—the data mining part , and theway to carry out the method and related techniques emphatically. When choosing the data mining algorithm, by careful analysis and researching, we found that for a long time, a category of Apriori -like algorithms has been adopted for mining frequent patterns. But they suffer from taking many scans of databases for huge number of candidate pattern occurrence frequencies checking. FP-tree algorithm adopts pattern fragment growth method and only scans database twice. It is about an order of magnitude faster than the Apriori algorithm. Finally, by using advanced JAVA, JSP techniques, the author has finished the project on web and puts forwardthe objective and ideas. By anglicizing of a large number of true data, got some useful experimental results .The results can be applied to practice and play a role in college management. And datasets analysis system based of the further improvement of the system. In the last part of the paper, we explore the foregrounds and prospects of data mining of association rules researches.