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：2013
卷号：3
期号：8
出版社：S.S. Mishra
摘要：In recent years, Data Mining is an important aspect for generating association rules among the large number of itemsets. Association Rule Mining is the method for discovering interesting relations between variables in large databases. It is considered as one of the important tasks of data mining intended towards decision making. Several association rule mining algorithms have been proposed to generate association rules from the given dataset. The most common algorithms of association rule mining are Apriori and FP-Growth. This paper presents the performance comparison of Apriori and FP-Growth algorithms. The two algorithms are compared based on the execution time and number of scans for different number of instances. The performance study shows that the FP-growth method is efficient and faster than the Apriori algorithm
