Dynamic Growing Data Mining of More Frequent Itemset in Large Database

Present data mining method have some disadvantages: when association relationship are mined between ID-set in database, information mined implies connection ID-set, but do not imply quantity relationship, otherwise, when recorders of database increase database is scanned repeat, system resources are wasted. In this paper mining algorithm is proposed about large database, more frequent itemsets, dynamic growing, that utilizes last mining result and information data of ID-set, can mine quantity relationship all ID-set in database, provides information guide to commerce and interflow of commodities to avoid decision mistakes. It is of importance about realizing modernization of interflow of commodities and some other application respect of data mining.