大型数据库中关于多频项集的动态增量式挖掘

提出了一种针对大型数据库、关于多频项集、动态增最式的挖掘新算法，利用前次的挖掘结果和新增物品项ID的明细数据，能有效地挖掘出频繁项集及各项ID之间的量化比例关系，给商家和物流系统提供信息指导，避免错误决策，对实现物流系统自动化及其它数据挖掘应用领域都具有极其重要的指导意义。

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.