DocumentCode
408317
Title
Mining association rules from relations on a parallel NCR teradata database system
Author
Chung, Soon M. ; Mangamuri, Murali
Author_Institution
Dept. of Comput. Sci. & Eng., Wright State Univ., Dayton, OH, USA
Volume
1
fYear
2004
fDate
5-7 April 2004
Firstpage
465
Abstract
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.
Keywords
data mining; parallel databases; relational databases; very large databases; SETM algorithm; mining association rules; parallel NCR teradata database system; relational data mining; Algorithm design and analysis; Association rules; Computer science; Data engineering; Data mining; Database systems; Itemsets; Performance analysis; Relational databases; Transaction databases;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology: Coding and Computing, 2004. Proceedings. ITCC 2004. International Conference on
Print_ISBN
0-7695-2108-8
Type
conf
DOI
10.1109/ITCC.2004.1286500
Filename
1286500
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