loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 1
Mining Association Rules from Relations on a Parallel NCR Teradata Database System
Las Vegas, Nevada
April 05-April 07
ISBN: 0-7695-2108-8
ASCII Text
x 
 
Soon M. Chung, Murali Mangamuri, "Mining Association Rules from Relations on a Parallel NCR Teradata Database System," Information Technology: Coding and Computing, International Conference on, vol. 1, pp. 465, International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 1, 2004.
 
 
BibTex
x
 
@article{ 10.1109/ITCC.2004.1286500,
author = {Soon M. Chung and Murali Mangamuri},
title = {Mining Association Rules from Relations on a Parallel NCR Teradata Database System},
journal ={Information Technology: Coding and Computing, International Conference on},
volume = {1},
year = {2004},
isbn = {0-7695-2108-8},
pages = {465},
doi = {http://doi.ieeecomputersociety.org/10.1109/ITCC.2004.1286500},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Information Technology: Coding and Computing, International Conference on
TI - Mining Association Rules from Relations on a Parallel NCR Teradata Database System
SN - 0-7695-2108-8
SP
EP
A1 - Soon M. Chung,
A1 - Murali Mangamuri,
PY - 2004
KW - data mining
KW - association rules
KW - parallel database system
KW - performance analysis
VL - 1
JA - Information Technology: Coding and Computing, International Conference on
ER -
 
Soon M. Chung, Wright State University, Dayton, Ohio
Murali Mangamuri, Wright State University, Dayton, Ohio
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 [Set-Oriented Mining for Association Rules in Relational Databases], 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.
Index Terms:
data mining, association rules, parallel database system, performance analysis
Citation:
Soon M. Chung, Murali Mangamuri, "Mining Association Rules from Relations on a Parallel NCR Teradata Database System," itcc, vol. 1, pp.465, International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 1, 2004
Usage of this product signifies your acceptance of the Terms of Use.