Title :
Estimating itemsets of interest by sampling
Author :
Zhang, Shichao ; Zhang, Chengqi
Author_Institution :
Sch. of Comput. & Math., Deakin Univ., Geelong, Vic., Australia
fDate :
6/23/1905 12:00:00 AM
Abstract :
Many applications such as marketing and stock investment may be time limited and few considerations to accurate itemsets. For these applications, we present a mining model to quickly estimate the approximate support of frequent itemsets of interest in large scale databases in this paper. An efficient algorithm is thus designed to reduce the searched space by pruning uninterested frequent itemsets
Keywords :
data mining; very large databases; data mining model; efficient algorithm; itemset estimation; itemset pruning; large scale databases; marketing; sampling; stock investment; time limited applications; Association rules; Australia; Data mining; Investments; Itemsets; Large-scale systems; Mathematics; Sampling methods; Time measurement; Transaction databases;
Conference_Titel :
Fuzzy Systems, 2001. The 10th IEEE International Conference on
Conference_Location :
Melbourne, Vic.
Print_ISBN :
0-7803-7293-X
DOI :
10.1109/FUZZ.2001.1007264
