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» Self-Similar Mining of Time Association Rules
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RCIS
2010
13 years 9 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
AUSAI
2005
Springer
14 years 4 months ago
K-Optimal Pattern Discovery: An Efficient and Effective Approach to Exploratory Data Mining
Most data-mining techniques seek a single model that optimizes an objective function with respect to the data. In many real-world applications several models will equally optimize...
Geoffrey I. Webb
SAC
2002
ACM
13 years 10 months ago
The P-tree algebra
The Peano Count Tree (P-tree) is a quadrant-based lossless tree representation of the original spatial data. The idea of P-tree is to recursively divide the entire spatial data, s...
Qin Ding, Maleq Khan, Amalendu Roy, William Perriz...
ICDM
2005
IEEE
177views Data Mining» more  ICDM 2005»
14 years 4 months ago
Average Number of Frequent (Closed) Patterns in Bernouilli and Markovian Databases
In data mining, enumerate the frequent or the closed patterns is often the first difficult task leading to the association rules discovery. The number of these patterns represen...
Loïck Lhote, François Rioult, Arnaud S...
DASFAA
2007
IEEE
234views Database» more  DASFAA 2007»
14 years 5 months ago
Estimating Missing Data in Data Streams
Networks of thousands of sensors present a feasible and economic solution to some of our most challenging problems, such as real-time traffic modeling, military sensing and trackin...
Nan Jiang, Le Gruenwald