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» Minimal Data Upgrading to Prevent Inference and Association
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ICDM
2002
IEEE
153views Data Mining» more  ICDM 2002»
13 years 10 months ago
Generating an informative cover for association rules
Mining association rules may generate a large numbers of rules making the results hard to analyze manually. Pasquier et al. have discussed the generation of GuiguesDuquenne–Luxe...
Laurentiu Cristofor, Dan A. Simovici
COGSCI
2010
107views more  COGSCI 2010»
13 years 5 months ago
Inferring Hidden Causal Structure
We used a new method to assess how people can infer unobserved causal structure from patterns of observed events. Participants were taught to draw causal graphs, and then shown a ...
Tamar Kushnir, Alison Gopnik, Chris Lucas, Laura S...
VLDB
2007
ACM
111views Database» more  VLDB 2007»
13 years 11 months ago
Security in Outsourcing of Association Rule Mining
Outsourcing association rule mining to an outside service provider brings several important benefits to the data owner. These include (i) relief from the high mining cost, (ii) m...
Wai Kit Wong, David W. Cheung, Edward Hung, Ben Ka...
DMKD
1997
ACM
198views Data Mining» more  DMKD 1997»
13 years 9 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...
IJFCS
2008
102views more  IJFCS 2008»
13 years 5 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...