This paper proposes a mining algorithm of all-weighted positive and negative association rules based on dynamic item weight

which can solve the problems of negative patterns mining based on dynamic item weight.This algorithm took the dynamic item weight dependent on transaction records into consideration

and adopted the itemset pruning method and pattern evaluation framework so as to discover effective all-weighted positive negative association rules via simple calculation and comparison of weight ratio and dimension ratio from the itemset.The experimental results show that this algorithm can prevent ineffective patterns

which makes the maximal declines of the mining time and number of the candidate itemsets by up to 94.09% and 88.16% respectively compared with the existing unweighted positive and negative association rule mining algorithms.