文章基本信息

标题：Mining frequent item sets without candidate generation using FP-Trees
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作者：G.Nageswara Rao ; Suman Kumar Gurram
期刊名称：International Journal of Computer Science and Information Technologies
电子版ISSN：0975-9646
出版年度：2011
卷号：2
期号：6
页码：2677-2685
出版社：TechScience Publications
摘要：There are so many algorithms for extracting frequent item sets.. These are very important for mining association rules as well as for many other data mining tasks . So many methods have been implemented for mining frequent item sets using a prefix tree structure known as frequent Pattern Tree (FP-Tree) for storing all the information about frequent item sets. In this paper we propose a new technique called fp-array technique based on FP-Tree Data structure, that reduces the traverse time of FPTrees and we can improve the performance of FP-Tree based algorithms. This FP-array technique will give the good results for sparse data sets. It consumes more memory when we use the sparse data sets , consumes less memory for dense data sets and the performance of this algorithm is very well when the minimum support is low
关键词：frequent Pattern - Tree; frequent item sets;association rules.