关键词: 数据挖掘, 负关联规则, 频繁项集, 非频繁项集

Abstract: Studying on the characteristic of negative association rules，this paper introduces vector inner product to this field，and puts forward a new algorithm to mining positive and negative association rules with multiple minimum supports based on vector inner product.Considering the inhomogeneous distribution of each itemset in transaction database，which may lead to the single minimum support is difficult to be set，it designs an algorithm that can mine frequent and infrequent itemsets，and mine positive and negative association rules from these itemsets with multiple minimum supports.Experimental results show that this method not only scans the database only once，but also has virtues such as pruning dynamically，without saving mid items，and saving lots of memories，which is important to the negative association rule mining in transaction database.

Key words: data mining, negative association rules, frequent itemsets, infrequent itemsets