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» Mining frequent itemsets in time-varying data streams
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PPOPP
2005
ACM
15 years 3 months ago
A sampling-based framework for parallel data mining
The goal of data mining algorithm is to discover useful information embedded in large databases. Frequent itemset mining and sequential pattern mining are two important data minin...
Shengnan Cong, Jiawei Han, Jay Hoeflinger, David A...
CORR
2011
Springer
222views Education» more  CORR 2011»
14 years 1 months ago
A New Data Layout For Set Intersection on GPUs
Abstract—Set intersection is the core in a variety of problems, e.g. frequent itemset mining and sparse boolean matrix multiplication. It is well-known that large speed gains can...
Rasmus Resen Amossen, Rasmus Pagh
CINQ
2004
Springer
125views Database» more  CINQ 2004»
15 years 3 months ago
Deducing Bounds on the Support of Itemsets
Mining Frequent Itemsets is the core operation of many data mining algorithms. This operation however, is very data intensive and sometimes produces a prohibitively large output. I...
Toon Calders
ADBIS
2003
Springer
108views Database» more  ADBIS 2003»
15 years 2 months ago
Evaluation of Common Counting Method for Concurrent Data Mining Queries
Data mining queries are often submitted concurrently to the data mining system. The data mining system should take advantage of overlapping of the mined datasets. In this paper we ...
Marek Wojciechowski, Maciej Zakrzewicz
PODS
2009
ACM
134views Database» more  PODS 2009»
15 years 10 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...