文章基本信息

标题：Efficient Tree-based Discovery of Frequent Itemsets
本地全文：下载
作者：Byung Joon Park
期刊名称：International Journal of Multimedia and Ubiquitous Engineering
印刷版ISSN：1975-0080
出版年度：2012
卷号：7
期号：2
出版社：SERSC
摘要：Various types of data structures and algorithms have been proposed to extract frequently occurring patterns from a given data set. In particular, several tree structures have been devised to represent the input data set for efficient pattern discovery. One of the fastest frequent pattern mining algorithms known to date is the CATS algorithm, which can efficiently represent the whole data set and allow mining with a single scan over the database. In this paper, we propose an efficient tree structure and its associated algorithm that provides a considerable performance improvement over CATS in terms of memory usage and processing time. We have demonstrated the effectiveness of our algorithm and performance improvement over the existing approach by a series of experiments.
关键词：frequent itemset; pattern discovery; tree structure