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» Mining Quantitative Associations in Large Database
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TEC
2008
104views more  TEC 2008»
13 years 9 months ago
Genetic-Fuzzy Data Mining With Divide-and-Conquer Strategy
Data mining is most commonly used in attempts to induce association rules from transaction data. Most previous studies focused on binary-valued transaction data. Transaction data i...
Tzung-Pei Hong, Chun-Hao Chen, Yeong-Chyi Lee, Yu-...
KAIS
2006
164views more  KAIS 2006»
13 years 9 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
ICDM
2007
IEEE
155views Data Mining» more  ICDM 2007»
14 years 1 months ago
Transitional Patterns and Their Significant Milestones
Mining frequent patterns in transaction databases has been studied extensively in data mining research. However, most of the existing frequent pattern mining algorithms do not con...
Qian Wan, Aijun An
PAKDD
2005
ACM
128views Data Mining» more  PAKDD 2005»
14 years 3 months ago
A Two-Phase Algorithm for Fast Discovery of High Utility Itemsets
Traditional association rules mining cannot meet the demands arising from some real applications. By considering the different values of individual items as utilities, utility mini...
Ying Liu, Wei-keng Liao, Alok N. Choudhary
ICTAI
2003
IEEE
14 years 3 months ago
Parallel Mining of Maximal Frequent Itemsets from Databases
In this paper, we propose a parallel algorithm for mining maximal frequent itemsets from databases. A frequent itemset is maximal if none of its supersets is frequent. The new par...
Soon Myoung Chung, Congnan Luo