文章基本信息

标题：A Survey of Frequent and Infrequent Weighted Itemset Mining Approaches
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作者：J.Jaya ; S.V.Hemalatha
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2014
卷号：2
期号：10
出版社：S&S Publications
摘要：Itemset mining is a data mining method extensively used for learning important correlations among data.Initially itemsets mining was made on discovering frequent itemsets. Frequent weighted item set characterizes data inwhich items may weight differently through frequent correlations in data’s. But, in some situations, for instance certaincost functions need to be minimized for determining rare data correlations. Determining these types of data is morechallenge and interesting research than mining frequent data in items. This paper surveys various methods for frequentitemset and infrequent item set mining of data. This work differentiates various methods with each other during miningof data. Finally, comparative measures of each method are presented which provides the significance and limitations offrequent and infrequent mining of data in itemsets.
关键词：Clustering; association rules; frequent itemset mining; infrequent itemset mining