TY - GEN
T1 - Discovery of weighted association rules mining
AU - Kumar, Preetham
AU - Ananthanarayana, V. S.
PY - 2010/5/28
Y1 - 2010/5/28
N2 - Mining of association rules for basket databases, has been investigated by [1] [3] [4], [9], [12], etc. Most of these works focus on mining binary association rules, i.e, most of the association rules mining algorithms to discover frequent itemsets do not consider the quantity in which items have been purchased. This paper discusses an efficient method for discovering a weighted association rules from a large volumes of data in a single scan of the database. The data structure used here is called Weighted Tree. We found that this algorithm is more efficient than Cai's Algorithm.
AB - Mining of association rules for basket databases, has been investigated by [1] [3] [4], [9], [12], etc. Most of these works focus on mining binary association rules, i.e, most of the association rules mining algorithms to discover frequent itemsets do not consider the quantity in which items have been purchased. This paper discusses an efficient method for discovering a weighted association rules from a large volumes of data in a single scan of the database. The data structure used here is called Weighted Tree. We found that this algorithm is more efficient than Cai's Algorithm.
UR - https://www.scopus.com/pages/publications/77952623342
UR - https://www.scopus.com/pages/publications/77952623342#tab=citedBy
U2 - 10.1109/ICCAE.2010.5451339
DO - 10.1109/ICCAE.2010.5451339
M3 - Conference contribution
AN - SCOPUS:77952623342
SN - 9781424455850
VL - 5
T3 - 2010 The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010
SP - 718
EP - 722
BT - 2010 The 2nd International Conference on Computer and Automation Engineering, ICCAE 2010
T2 - 2nd International Conference on Computer and Automation Engineering, ICCAE 2010
Y2 - 26 February 2010 through 28 February 2010
ER -