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» Mining Frequent Itemsets Using Support Constraints
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SDM
2007
SIAM
106views Data Mining» more  SDM 2007»
13 years 9 months ago
Approximating Representations for Large Numerical Databases
The paper introduces a notion of support for realvalued functions. It is shown how to approximate supports of a large class of functions based on supports of so called polynomial ...
Szymon Jaroszewicz, Marcin Korzen
ICMLA
2009
13 years 5 months ago
All-Monotony: A Generalization of the All-Confidence Antimonotony
Abstract--Many studies have shown the limits of support/confidence framework used in Apriori-like algorithms to mine association rules. One solution to cope with this limitation is...
Yannick Le Bras, Philippe Lenca, Sorin Moga, St&ea...
DMKD
1997
ACM
198views Data Mining» more  DMKD 1997»
13 years 11 months ago
Clustering Based On Association Rule Hypergraphs
Clustering in data mining is a discovery process that groups a set of data such that the intracluster similarity is maximized and the intercluster similarity is minimized. These d...
Eui-Hong Han, George Karypis, Vipin Kumar, Bamshad...
KES
2008
Springer
13 years 7 months ago
Data Mining for Navigation Generating System with Unorganized Web Resources
Users prefer to navigate subjects from organized topics in an abundance resources than to list pages retrieved from search engines. We propose a framework to cluster frequent items...
Diana Purwitasari, Yasuhisa Okazaki, Kenzi Watanab...
PODS
2006
ACM
217views Database» more  PODS 2006»
14 years 7 months ago
A simpler and more efficient deterministic scheme for finding frequent items over sliding windows
In this paper, we give a simple scheme for identifying approximate frequent items over a sliding window of size n. Our scheme is deterministic and does not make any assumption on ...
Lap-Kei Lee, H. F. Ting