文章基本信息

标题：Comparison of FP-Tree and B-Tree in Data Mining
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作者：Pallavi Sharma ; Lokesk Kumar Joshi
期刊名称：International Journal of Advanced Research In Computer Science and Software Engineering
印刷版ISSN：2277-6451
电子版ISSN：2277-128X
出版年度：2012
卷号：2
期号：2
出版社：S.S. Mishra
摘要：Association rule mining, one of the most important and well researched techniques of data mining, was first introduced in. It aims to extract interesting correlations, frequent patterns, associations or casual structures among sets of items in the transaction databases or other data repositories.. However, no method has been shown to be able to handle data streams, as no method is scalable enough to manage the high rate which stream data arrive at. More recently, they have received attention from the data mining community and methods have been defined to automatically extract and maintain gradual rules from numerical databases. In this paper, we thus propose an original approach to mine data streams for Association rule mining. Our method is based on B-Trees and FP growth in order to speed up the process. B-Trees are used to store already-known for order to maintain the knowledge over time and provide a fast way to disca rd non relevant data while FP growth.