关键词: 正负关联规则，关联规则挖掘，最大频繁项集，置信差

Abstract: Aiming at the problems of the traditional positive and negative association rules, such as multi-scanning database and generating large candidate frectuent itemset,on the basis of comparing recent research on association rules mining,put forward an improved positive and negative association rules mining algorithm, which can accomplish mining positive and negative association rules by scanning Dataset twice;and improve the algorithm of mining the maximal frequcnt itemset, which result in upgrading the efficiency of the algorithm; besides, improve the standard of confidence level,in order to increase the quality of association rules mining.

Key words: Positive and negative association rules,Association rules mining,Maximal frequent itemset,D-value of confidence level