文章基本信息

标题：A Collaborative Approach of Frequent Item Set Mining: A Survey
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作者：Arpan Shah ; Pratik Patel
期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2015
卷号：15
期号：11
页码：49-52
出版社：International Journal of Computer Science and Network Security
摘要：Data mining defines hidden pattern in data sets and association between the patterns. In data mining, association rule mining is key techniques for discovering useful patterns from large collection of data. Frequent iemset mining is a step of association rule mining. Frequent itemset mining is used to gather itemsets after discovering association rules. In this paper, we have explained fundamentals of frequent itemset mining. We have defined present��s techniques for frequent item set mining. From the large variety of capable algorithms that have been established we will compare the most important ones. We will organize the algorithms and investigate their run time performance.
关键词：Data mining; Association Rules; Frequent Item set Mining; FP- growth; Minimum Support