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ADC
2003
Springer
182views Database» more  ADC 2003»
13 years 10 months ago
CT-ITL : Efficient Frequent Item Set Mining Using a Compressed Prefix Tree with Pattern Growth
Discovering association rules that identify relationships among sets of items is an important problem in data mining. Finding frequent item sets is computationally the most expens...
Yudho Giri Sucahyo, Raj P. Gopalan
SDM
2009
SIAM
176views Data Mining» more  SDM 2009»
14 years 2 months ago
Discovery of Geospatial Discriminating Patterns from Remote Sensing Datasets.
Large amounts of remotely sensed data calls for data mining techniques to fully utilize their rich information content. In this paper, we study new means of discovery and summariz...
Wei Ding 0003, Tomasz F. Stepinski, Josue Salazar
AUSDM
2008
Springer
235views Data Mining» more  AUSDM 2008»
13 years 6 months ago
ShrFP-Tree: An Efficient Tree Structure for Mining Share-Frequent Patterns
Share-frequent pattern mining discovers more useful and realistic knowledge from database compared to the traditional frequent pattern mining by considering the non-binary frequen...
Chowdhury Farhan Ahmed, Syed Khairuzzaman Tanbeer,...
ICDE
2006
IEEE
222views Database» more  ICDE 2006»
14 years 6 months ago
CLAN: An Algorithm for Mining Closed Cliques from Large Dense Graph Databases
Most previously proposed frequent graph mining algorithms are intended to find the complete set of all frequent, closed subgraphs. However, in many cases only a subset of the freq...
Jianyong Wang, Zhiping Zeng, Lizhu Zhou
ICDM
2005
IEEE
125views Data Mining» more  ICDM 2005»
13 years 10 months ago
A Thorough Experimental Study of Datasets for Frequent Itemsets
The discovery of frequent patterns is a famous problem in data mining. While plenty of algorithms have been proposed during the last decade, only a few contributions have tried to...
Frédéric Flouvat, Fabien De Marchi, ...