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ICDM
2009
IEEE
139views Data Mining» more  ICDM 2009»
13 years 5 months ago
Frequent Pattern Discovery from a Single Graph with Quantitative Itemsets
In this paper, we focus on a single graph whose vertices contain a set of quantitative attributes. Several networks can be naturally represented in this complex graph. An example i...
Yuuki Miyoshi, Tomonobu Ozaki, Takenao Ohkawa
KAIS
2006
164views more  KAIS 2006»
13 years 7 months ago
On efficiently summarizing categorical databases
Frequent itemset mining was initially proposed and has been studied extensively in the context of association rule mining. In recent years, several studies have also extended its a...
Jianyong Wang, George Karypis
PAKDD
2007
ACM
121views Data Mining» more  PAKDD 2007»
14 years 1 months ago
Two-Phase Algorithms for a Novel Utility-Frequent Mining Model
When companies seek for the combination of products which can constantly generate high profit, the association rule mining (ARM) or the utility mining will not achieve such task. ...
Jieh-Shan Yeh, Yu-Chiang Li, Chin-Chen Chang
RCIS
2010
13 years 6 months ago
A Tree-based Approach for Efficiently Mining Approximate Frequent Itemsets
—The strategies for mining frequent itemsets, which is the essential part of discovering association rules, have been widely studied over the last decade. In real-world datasets,...
Jia-Ling Koh, Yi-Lang Tu
FIMI
2004
175views Data Mining» more  FIMI 2004»
13 years 9 months ago
CT-PRO: A Bottom-Up Non Recursive Frequent Itemset Mining Algorithm Using Compressed FP-Tree Data Structure
Frequent itemset mining (FIM) is an essential part of association rules mining. Its application for other data mining tasks has also been recognized. It has been an active researc...
Yudho Giri Sucahyo, Raj P. Gopalan