Mining Associations Rules on a NCR Teradata System

Mining Associations Rules on a NCR Teradata System

Soon M. Chung (Wright State University, USA) and Murali Mangamuri (Wright State University, USA)
Copyright: © 2005 |Pages: 6
DOI: 10.4018/978-1-59140-557-3.ch142
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Data mining from relations is becoming increasingly important with the advent of parallel database systems. In this paper, we propose a new algorithm for mining association rules from relations. The new algorithm is an enhanced version of the SETM algorithm (Houtsma & Swami 1995), and it reduces the number of candidate itemsets considerably. We implemented and evaluated the new algorithm on a parallel NCR Teradata database system. The new algorithm is much faster than the SETM algorithm, and its performance is quite scalable.

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