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http://dx.doi.org/10.3745/KIPSTD.2008.15-D.1.15

Frequent Patterns Mining using only one-time Database Scan  

Chai, Duck-Jin (충북대학교 BK21)
Jin, Long (한국전자통신연구원)
Lee, Yong-Mi (충북대학교 전자계산학과)
Hwang, Bu-Hyun (전남대학교 전산학과)
Ryu, Keun-Ho (충북대학교 전기전자 및 컴퓨터공학부)
Publication Information
The KIPS Transactions:PartD / v.15D, no.1, 2008 , pp. 15-22 More about this Journal
Abstract
In this paper, we propose an efficient algorithm using only one-time database scan. The proposed algorithm creates the bipartite graph which indicates relationship of large items and transactions including the large items. And then we can find large itemsets using the bipartite graph. The bipartite graph is generated when database is scanned to find large items. We can't easily find transactions which include large items in the large database. In the bipartite graph, large items and transactions are linked each other. So, we can trace the transactions which include large items through the link information. Therefore the bipartite graph is a indexed database which indicates inclusion relationship of large items and transactions. We can fast find large itemsets because proposed method conducts only one-time database scan and scans indexed the bipartite graph. Also, it don't generate candidate itemsets.
Keywords
Data Mining; Association Rule; Bipartite Graph;
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