期刊名称:International Journal of Computer Science & Technology
印刷版ISSN:2229-4333
电子版ISSN:0976-8491
出版年度:2012
卷号:3
期号:1
页码:489-493
语种:English
出版社:Ayushmaan Technologies
摘要:In this paper we present new scheme for extracting associationrules that considers the time, number of database scans, memoryconsumption, and the interestingness of the rules. Discover a FISdata mining association algorithm that removes the disadvantagesof APRIORI algorithm and is effcient in terms of number ofdatabase scan and time. The frequent patterns algorithm withoutcandidate generation eliminates the costly candidate generation.It also avoids scanning the database again and again. So, weuse Frequent Pattern (FP) Growth ARM algorithm that is moreeffcient structure to mine patterns when database grows.