Research And Application Of Data Mining Algorithm Of Association Rules

The development of data mining is catering to the trend of the large data information times, new technology from a professional fields is proposed to widely used means of mature business model application.Because of the increasing of the scale of the data in each field of industryscale, abstract data types also become more complex, data mining plays an important role in large scale exploiting hidden rules in the data and the value of information.Bank is the most important part of the financial system, with other trade can not match the user scale, the amount of data generated and the scale of complexity is very great. While banks in the control of the capital, it is necessary to customer data through data mining technology with a deep-seated analysis and systemic treatment. Master the situation of users in the banking and capital,through the tfficient algorithm of data mining technology to get the business development of the bank’s most valuable information.This paper is based on the data mining association rules theory especially for the systematic research on association rules mining, the concept, process,properties and the core algorithm is outlined and illustrated. At the same time, the detailed analysis of the classical Apriori algorithm, and aiming at the scanning database performance problems and too many invalid candidate itemsets scale characteristics of optimization, an improved algorithm called Apriori_Reduce is proposed, the performance test of two kinds of algorithms are compared, and applied in the bank customer information analysis. For banks with decision support value rules in the customer’s business information and capital related information.