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» Probabilistic frequent itemset mining in uncertain databases
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KAIS
2008
114views more  KAIS 2008»
13 years 7 months ago
A new concise representation of frequent itemsets using generators and a positive border
A complete set of frequent itemsets can get undesirably large due to redundancy when the minimum support threshold is low or when the database is dense. Several concise representat...
Guimei Liu, Jinyan Li, Limsoon Wong
CINQ
2004
Springer
125views Database» more  CINQ 2004»
14 years 1 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
ICDE
2000
IEEE
118views Database» more  ICDE 2000»
14 years 9 months ago
Mining Recurrent Items in Multimedia with Progressive Resolution Refinement
Despite the overwhelming amounts of multimedia data recently generated and the significance of such data, very few people have systematically investigated multimedia data mining. ...
Hua Zhu, Jiawei Han, Osmar R. Zaïane
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...
FIMI
2004
161views Data Mining» more  FIMI 2004»
13 years 9 months ago
ABS: Adaptive Borders Search of frequent itemsets
In this paper, we present an ongoing work to discover maximal frequent itemsets in a transactional database. We propose an algorithm called ABS for Adaptive Borders Search, which ...
Frédéric Flouvat, Fabien De Marchi, ...