计算机工程与应用2011，Vol.47Issue(36)：162-165,189,5.DOI:10.3778/j.issn.1002-8331.2011.36.045
向量内积策略的多支持度正负关联规则挖掘
Study on mining positive and negative association rules based on vector inner product
刘彩虹 1刘强2
作者信息
- 1. 大连外国语学院现代教育技术中心,辽宁大连116044
- 2. 海军91423部队
- 折叠
摘要
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 productConsidering 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.关键词
数据挖掘/负关联规则/频繁项集/非频繁项集Key words
data mining/negative association rules/ frequent itemsets/ infrequent itemsets分类
信息技术与安全科学引用本文复制引用
刘彩虹,刘强..向量内积策略的多支持度正负关联规则挖掘[J].计算机工程与应用,2011,47(36):162-165,189,5.
