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KDD
2009
ACM
229views Data Mining» more  KDD 2009»
16 years 3 months ago
Relational learning via latent social dimensions
Social media such as blogs, Facebook, Flickr, etc., presents data in a network format rather than classical IID distribution. To address the interdependency among data instances, ...
Lei Tang, Huan Liu
KDD
2008
ACM
147views Data Mining» more  KDD 2008»
16 years 2 months ago
Structured learning for non-smooth ranking losses
Learning to rank from relevance judgment is an active research area. Itemwise score regression, pairwise preference satisfaction, and listwise structured learning are the major te...
Soumen Chakrabarti, Rajiv Khanna, Uma Sawant, Chir...
KDD
2006
ACM
155views Data Mining» more  KDD 2006»
16 years 2 months ago
Camouflaged fraud detection in domains with complex relationships
We describe a data mining system to detect frauds that are camouflaged to look like normal activities in domains with high number of known relationships. Examples include accounti...
Sankar Virdhagriswaran, Gordon Dakin
KDD
2004
ACM
126views Data Mining» more  KDD 2004»
16 years 2 months ago
Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage
We present and empirically analyze a machine-learning approach for detecting intrusions on individual computers. Our Winnowbased algorithm continually monitors user and system beh...
Jude W. Shavlik, Mark Shavlik
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
16 years 2 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger
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