Research Of Data Mining In Credit Card Market

It considers that Association Rules is one of the most important and extensive use algorithm in research of data mining in credit card market. We analyse and research Apriori algorithm which has been widely used in data mining of credit card market and discover that Apriori algorithm has to produce many temporary itemsets and visit database too much. In order to come over the the fault of Apriori algorithm,this thesis puts forward the FP_growth algorithm.we discover the FP_growth algorithm is more effective than Apriori algorithm. On the base of research of Association Rules FP_growth algorithm ,this thesis has done some research of data mining in credit card market at first,expecially done extensive research into consuming action of custom and personal sale and puts forwards new credit card market method .At same time, we find that traditional data mining structure based on C/S has not met the need of new use of credit card market like the bank of Internet and the bank of mobile phone which are the important part of credit card market.In order to solve the problem, this thesis puts forward the data mining structure based on B/S.At last ,we take FP_growth algorithm into data mining system of credit card market which is structure of B/S.