文章基本信息

标题：Efficient Algorithms for Mining Rare Itemset over Time Variant Transactional Database
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作者：Nidhi Sethi ; Pradeep Sharma
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2014
卷号：5
期号：3
页码：3465-3468
出版社：TechScience Publications
摘要：frequent itemset mining is an important data mining task to discover the hidden, interesting pattern of items in the database. The rare itemsets are those items which appear infrequently in the database. Sometimes rare itemsets are more important as they carry useful information which frequent patterns may not give. Rare itemset appear only when threshold is set to very low. Rare itemsets are also important in finding associations between infrequently purchased (e.g. expensive or high-profit) retail items, analysis of biomedical data as rare patterns help the doctors to find the disease with rare set of symptoms. Rare itemset mining is a challenging task. There are two important issues in mining rare itemsets. (i) How to identify interesting rare patterns. (ii) How to efficiently discover them in large dynamic datasets. In this paper we present an efficient approach for mining rare item set for time variant dynamic data set
关键词：Frequent itemset; rare itemset; threshold; high;profit; hidden pattern