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Mining association rules from relations on a parallel NCR teradata database system

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2 Author(s)
Chung, S.M. ; Dept. of Comput. Sci. & Eng., Wright State Univ., Dayton, OH, USA ; Mangamuri, M.

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 of M. Houtsma and A. 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.

Published in:
Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004. International Conference on  (Volume:1 )

Date of Conference: 5-7 April 2004

Page(s):
465 - 470 Vol.1
Print ISBN:
0-7695-2108-8
INSPEC Accession Number:
8082295
Digital Object Identifier :
10.1109/ITCC.2004.1286500
Product Type:
Conference Publications

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