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KAIS
2006
164views more  KAIS 2006»
13 years 4 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
KDD
1998
ACM
147views Data Mining» more  KDD 1998»
13 years 9 months ago
ADtrees for Fast Counting and for Fast Learning of Association Rules
Abstract: The problem of discovering association rules in large databases has received considerable research attention. Much research has examined the exhaustive discovery of all a...
Brigham S. Anderson, Andrew W. Moore
AUSDM
2007
Springer
193views Data Mining» more  AUSDM 2007»
13 years 11 months ago
Are Zero-suppressed Binary Decision Diagrams Good for Mining Frequent Patterns in High Dimensional Datasets?
Mining frequent patterns such as frequent itemsets is a core operation in many important data mining tasks, such as in association rule mining. Mining frequent itemsets in high-di...
Elsa Loekito, James Bailey
ACSC
2008
IEEE
13 years 6 months ago
An efficient hash-based algorithm for minimal k-anonymity
A number of organizations publish microdata for purposes such as public health and demographic research. Although attributes of microdata that clearly identify individuals, such a...
Xiaoxun Sun, Min Li, Hua Wang, Ashley W. Plank
KDD
2010
ACM
235views Data Mining» more  KDD 2010»
13 years 8 months ago
Direct mining of discriminative patterns for classifying uncertain data
Classification is one of the most essential tasks in data mining. Unlike other methods, associative classification tries to find all the frequent patterns existing in the input...
Chuancong Gao, Jianyong Wang