期刊名称:International Journal of Computer Science and Network Security
印刷版ISSN:1738-7906
出版年度:2009
卷号:9
期号:5
页码:266-272
出版社:International Journal of Computer Science and Network Security
摘要:Finding frequent itemsets in databases is crucial in data mining for purpose of extracting association rules. Many algorithms were developed to find those frequent itemsets. This paper presents a summarization and a comparative study of the available FP-growth algorithm variations produced for mining frequent itemsets showing their capabilities and efficiency in terms of time and memory consumption.