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KDD
2009
ACM
296views Data Mining» more  KDD 2009»
16 years 7 months ago
Anonymizing healthcare data: a case study on the blood transfusion service
: Gaining access to high-quality health data is a vital requirement to informed decision making for medical practitioners and pharmaceutical researchers. Driven by mutual benefits ...
Noman Mohammed, Benjamin C. M. Fung, Patrick C. K....
KDD
2008
ACM
137views Data Mining» more  KDD 2008»
16 years 6 months ago
Learning classifiers from only positive and unlabeled data
The input to an algorithm that learns a binary classifier normally consists of two sets of examples, where one set consists of positive examples of the concept to be learned, and ...
Charles Elkan, Keith Noto
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
16 years 6 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
2008
ACM
174views Data Mining» more  KDD 2008»
16 years 6 months ago
Automatic identification of quasi-experimental designs for discovering causal knowledge
Researchers in the social and behavioral sciences routinely rely on quasi-experimental designs to discover knowledge from large databases. Quasi-experimental designs (QEDs) exploi...
David D. Jensen, Andrew S. Fast, Brian J. Taylor, ...
KDD
2008
ACM
150views Data Mining» more  KDD 2008»
16 years 6 months ago
Hypergraph spectral learning for multi-label classification
A hypergraph is a generalization of the traditional graph in which the edges are arbitrary non-empty subsets of the vertex set. It has been applied successfully to capture highord...
Liang Sun, Shuiwang Ji, Jieping Ye
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