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ICICS
2005
Springer
14 years 1 months ago
Private Itemset Support Counting
Private itemset support counting (PISC) is a basic building block of various privacy-preserving data mining algorithms. Briefly, in PISC, Client wants to know the support of her i...
Sven Laur, Helger Lipmaa, Taneli Mielikäinen
IJFCS
2008
102views more  IJFCS 2008»
13 years 7 months ago
Succinct Minimal Generators: Theoretical Foundations and Applications
In data mining applications, highly sized contexts are handled what usually results in a considerably large set of frequent itemsets, even for high values of the minimum support t...
Tarek Hamrouni, Sadok Ben Yahia, Engelbert Mephu N...
CINQ
2004
Springer
125views Database» more  CINQ 2004»
14 years 1 months ago
The Hows, Whys, and Whens of Constraints in Itemset and Rule Discovery
Many researchers in our community (this author included) regularly emphasize the role constraints play in improving performance of data-mining algorithms. This emphasis has led to ...
Roberto J. Bayardo
FIMI
2003
210views Data Mining» more  FIMI 2003»
13 years 9 months ago
COFI-tree Mining: A New Approach to Pattern Growth with Reduced Candidacy Generation
Existing association rule mining algorithms suffer from many problems when mining massive transactional datasets. Some of these major problems are: (1) the repetitive I/O disk sca...
Osmar R. Zaïane, Mohammad El-Hajj
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...