e-NFIS: Efficient Negative Frequent Itemsets Mining only based on Positive Ones

摘要：

Negative association rules (NAR) mining, which has played important roles in real applications, mainly focuses on the form A→B, A→B, --A→B and -A→-B so far, where A (e.g. (a1a2)) and B (e.g. (b1b2)) are occurring itemsets. Another form of negative association rules, such as a1-a2→b1-b2, which contain occurring (or positive) items and nonoccurring (or negative) items, can also reflect the relations of itemsets from another angle. The first step to mine this form of NAR is to mine negative frequent itemsets (NFIS). This paper mainly focuses on this step and proposes a novel method, e-NFIS (efficient negative frequent itemsets), to mine NFIS. The main idea of e-NFIS is to mine NFIS only from positive frequent itemsets (PFIS). E-NFIS contains three aspects: 1) using traditional method to mine PFIS; 2) an efficient method to generate negative candidate itemsets from PFIS; 3) calculate the support of negative candidate itemsets only using the support of PFIS, without additional database scanning. Experimental results show that the e-NFIS is efficient

关键词： positive frequent itemsets negative frequent itemsets negative association rule

作者: Xiangjun Dong Liang Ma Xiqing Han

作者单位: School of Information Science and Technology, Shandong Polytechnic University, Jinan 250353, China Administration Office, Shandong Institute of Commerce and Technology, Jinan 250353, China

会议类型: 国际会议

会议名称: 2011 International Conference on Information and Computer Networks(ICICN 2011)(2011年信息与计算机网络国际会议)

会议地点: 贵阳

会议语种:英文

页码: 517-519

在线出版日期: 2011-01-26（万方平台首次上网日期，不代表论文的发表时间）