Study And Application Of Data-mining Algorithm On Educational Decision Support System

With development of technology of information and network, teaching management system is becoming a important part of management in the university. Currently, these systems accumulate a lot of data related to student and course. The paper is based on these thousands of data and tries to analyze those data scientifically. Then using to impulse the development of teaching management work by contraries.Data mining and knowledge discovery in databases is drawing knowledge from the database, data warehouse or other databases. Data mining is a promising and flourishing frontier in database system and new database application. Data mining also popularly referred to as knowledge discovery in database (KDD); is the automated or convenient extraction of patterns representing knowledge implicitly stored in large database, data warehouses, and other massive information repositories. It is one of the international advanced directions in the field of database and information decision, and association of rules mining is one of key of Data Mining.After thorough research of data mining and its application, The paper mainly researches a new integrated data-mining model based on teaching decision support system. And based on the association and decision tree algorithm, this paper expands the algorithm to apply in teaching decision support system. The main research include:Firstly, A survey on technology of data mining and relative algorithm. Thorough research all kinds of data mining model, provided a new integrated data-mining model based on teaching decision support system. It can guide our teaching and management activity scientifically, and also can improve the quality of teaching and management..Secondly, Research several data mining algorithm, include association rules and decision tree, such as Aprrior, AprriorTid, ID3, C4.5. Based on this work and the feature of data of teaching and management, inventing a new improved algorithm.Finally, develop a new teaching decision support system, and verify the theory provided in this paper.