文章基本信息

标题：Graph Based New Approach for Frequent Pattern Mining
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作者：Anurag Choubey ; Ravindra Patel ; J.L. Rana 等
期刊名称：International Journal of Computer Science & Information Technology (IJCSIT)
印刷版ISSN：0975-4660
电子版ISSN：0975-3826
出版年度：2012
卷号：4
期号：1
页码：221
出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Association rule mining is a function of data mining research domain and frequent pattern mining is anessential part of it. Most of the previous studies on mining frequent patterns based on an Aprioriapproach, which required more number of database scans and operations for counting pattern supportsin the database. Since the size of each set of transaction may be massive that it makes difficult to performtraditional data mining tasks. This research intends to propose a graph structure that captures only thoseitemsets that needs to define a sufficiently immense dataset into a submatrix representing importantweights and does not give any chance to outliers. We have devised a strategy that covers significant factsof data by drilling down the large data into a succinct form of an Adjacency Matrix at different stages ofmining process. The graph structure is so designed that it can be easily maintained and the trade off incompressing the large data values is reduced. Experimental results show the effectiveness of our graphbased approach.
关键词：Data mining; Frequent pattern; Graph structure; Adjacency Matrix