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» Parallel Mining of Maximal Frequent Itemsets from Databases
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IDA
2008
Springer
13 years 7 months ago
Mining frequent items in a stream using flexible windows
We study the problem of finding frequent items in a continuous stream of itemsets. A new frequency measure is introduced, based on a flexible window length. For a given item, its ...
Toon Calders, Nele Dexters, Bart Goethals
PODS
2009
ACM
134views Database» more  PODS 2009»
14 years 8 months ago
An efficient rigorous approach for identifying statistically significant frequent itemsets
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is b...
Adam Kirsch, Michael Mitzenmacher, Andrea Pietraca...
LWA
2004
13 years 9 months ago
Efficient Frequent Pattern Mining in Relational Databases
Data mining on large relational databases has gained popularity and its significance is well recognized. However, the performance of SQL based data mining is known to fall behind ...
Xuequn Shang, Kai-Uwe Sattler, Ingolf Geist
ICPADS
2006
IEEE
14 years 1 months ago
Parallel Leap: Large-Scale Maximal Pattern Mining in a Distributed Environment
When computationally feasible, mining extremely large databases produces tremendously large numbers of frequent patterns. In many cases, it is impractical to mine those datasets d...
Mohammad El-Hajj, Osmar R. Zaïane
PKDD
2005
Springer
129views Data Mining» more  PKDD 2005»
14 years 1 months ago
Interestingness is Not a Dichotomy: Introducing Softness in Constrained Pattern Mining
Abstract. The paradigm of pattern discovery based on constraints was introduced with the aim of providing to the user a tool to drive the discovery process towards potentially inte...
Stefano Bistarelli, Francesco Bonchi