Application Of Improved Apriori Algorithm On Expansive Training To Cultivation Of Student Quality

The explosive growth of data in information society and the increasingly severe problems of "abundant data & scarce knowledge" pull the demands of powerful data analysis tools. Decision makers need to convert large volume of data into valuable information and knowledge. The emergence of data mining provides strong technical support for the urgent need.Mining for association rules is an important class of data mining, which is the process of extracting interesting and frequent patterns from the data. The aim of mining association rules is to find relations among items. Because of their wide applicability and usefulness in many areas such as supermarket transaction analysis, telecommunications, word occurrence in text documents, user's visit to WWW pages etc., they have therefore become a key data-mining .At first, this paper expatiates on Data Mining, Data Warehouse, Association Rules and some relative knowledge, than it pays more attentions to study the Apriori arithmetic. According to the limitation of the existing Apriori arithmetic, the paper puts forward an ameliorated arithmetic named 2STEPApriori arithmetic, which reduces the scanning of the Data Base.2STEPApriori arithmetic brings two frequent large aggregate during scanning the affair Data Base one time, it reduces the times of accessing Data Base and advances the efficiency of mining. The capability of 2STEPApriori is also analyzed.The paper finally designs the Diathesis Analysis System of the Academician base on the Data Warehouse and realizes the system, it makes use of the 2STEPApriori arithmetic and performs all right.