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  • 标题:A Survey of Frequent and Infrequent Weighted Itemset Mining Approaches
  • 本地全文:下载
  • 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
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