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» Randomization in Privacy-Preserving Data Mining
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ICICS
2005
Springer
14 years 4 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
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 11 months ago
Using ghost edges for classification in sparsely labeled networks
We address the problem of classification in partially labeled networks (a.k.a. within-network classification) where observed class labels are sparse. Techniques for statistical re...
Brian Gallagher, Hanghang Tong, Tina Eliassi-Rad, ...
KDD
2009
ACM
611views Data Mining» more  KDD 2009»
14 years 11 months ago
Fast approximate spectral clustering
Spectral clustering refers to a flexible class of clustering procedures that can produce high-quality clusterings on small data sets but which has limited applicability to large-s...
Donghui Yan, Ling Huang, Michael I. Jordan
KDD
2005
ACM
104views Data Mining» more  KDD 2005»
14 years 11 months ago
A hit-miss model for duplicate detection in the WHO drug safety database
The WHO Collaborating Centre for International Drug Monitoring in Uppsala, Sweden, maintains and analyses the world's largest database of reports on suspected adverse drug re...
Andrew Bate, G. Niklas Norén, Roland Orre
KDD
2007
ACM
148views Data Mining» more  KDD 2007»
14 years 11 months ago
Detecting research topics via the correlation between graphs and texts
In this paper we address the problem of detecting topics in large-scale linked document collections. Recently, topic detection has become a very active area of research due to its...
Yookyung Jo, Carl Lagoze, C. Lee Giles