期刊名称：International Journal on Computer Science and Engineering
印刷版ISSN：2229-5631
电子版ISSN：0975-3397
出版年度：2010
卷号：2
期号：5
页码：1700-1704
出版社：Engg Journals Publications
摘要：over the years, a variety of algorithms for finding frequent item sets in very large transaction databases have been developed. The problems of finding frequent item sets are basic in multi level association rule mining, fast algorithms for solving problems are needed. This paper presents an efficient version of apriori algorithm for mining multi-level association rules in large databases to finding maximum frequent itemset at lower level of abstraction. We propose a new, fast and an efficient algorithm (SC-BF Multilevel) with single scan of database for mining complete frequent item sets. To reduce the execution time and increase throughput in new method. Our proposed algorithm works well comparison with general approach of multilevel association rules.
关键词：Data mining; association rules; multilevel association rules; transaction database
