文章基本信息

标题：Rapid Update In Frequent Pattern form Large Dynamic Database to Increase Scalability
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作者：Abhay Mundra ; Poonam Tomar ; Deepak Kulhare 等
期刊名称：International Journal of Soft Computing & Engineering
电子版ISSN：2231-2307
出版年度：2013
卷号：2
期号：6
页码：307-310
出版社：International Journal of Soft Computing & Engineering
摘要：Association rule mining is a popular data mining technique which gives us valuable relationships among different items in a dataset. In dynamic databases, new transactions are appended as time advances. This may introduce new association rules and some existing association rules would become invalid [1]-[2]. Thus, the maintenance of association rules for dynamic databases is an important problem. Several incremental algorithms, is proposed to deal with this problem. In this paper we proposed algorithm RUPF (Rapid Update in Frequent Pattern). This algorithm reduces a number of times to scan the database (old and new) to generate frequent pattern. As a result, the algorithm has execution time faster than that of previous Algorithms. This paper also conducts experiments to show the performance of the proposed algorithm. The result shows that the proposed algorithm has a good performance.
关键词：Association rule; frequent pattern for Dynamic;maintenance; incremental algorithms.