TY - GEN
T1 - Strongest association rules mining for efficient applications
AU - Li, Jie
AU - Xu, Yong
AU - Wang, Yunfeng
AU - Chu, Chao Hsien
PY - 2007
Y1 - 2007
N2 - Rule explosion has become an important problem of association rules mining, as conventional mining algorithms often produce too many rules for decision makers to digest. In this paper, the notion of strongest association rules (SAR) is proposed for representing all association information with fewer rules, and a matrix-based algorithm is developed for mining SAR set. Our experiments show that the number of SAR is about 26% of the number of all rules in average, and the number does not monotonously increase with a smaller minimal confidence.
AB - Rule explosion has become an important problem of association rules mining, as conventional mining algorithms often produce too many rules for decision makers to digest. In this paper, the notion of strongest association rules (SAR) is proposed for representing all association information with fewer rules, and a matrix-based algorithm is developed for mining SAR set. Our experiments show that the number of SAR is about 26% of the number of all rules in average, and the number does not monotonously increase with a smaller minimal confidence.
UR - http://www.scopus.com/inward/record.url?scp=40549134171&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=40549134171&partnerID=8YFLogxK
U2 - 10.1109/ICSSSM.2007.4280170
DO - 10.1109/ICSSSM.2007.4280170
M3 - Conference contribution
AN - SCOPUS:40549134171
SN - 1424408857
SN - 9781424408856
T3 - Proceedings - ICSSSM'07: 2007 International Conference on Service Systems and Service Management
BT - Proceedings - ICSSSM'07
T2 - ICSSSM'07: 2007 International Conference on Service Systems and Service Management
Y2 - 9 June 2007 through 11 June 2007
ER -