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» Learning Classifiers from Semantically Heterogeneous Data
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SSDBM
2005
IEEE
100views Database» more  SSDBM 2005»
14 years 3 months ago
An Information Theoretic Model for Database Alignment
As with many large organizations, the Government's data is split in many different ways and is collected at different times by different people. The resulting massive data he...
Patrick Pantel, Andrew Philpot, Eduard H. Hovy
FUIN
2006
107views more  FUIN 2006»
13 years 9 months ago
Learning Sunspot Classification
Sunspots are the subject of interest to many astronomers and solar physicists. Sunspot observation, analysis and classification form an important part of furthering the knowledge a...
Trung Thanh Nguyen, Claire P. Willis, Derek J. Pad...
NIPS
2008
13 years 11 months ago
Unsupervised Learning of Visual Sense Models for Polysemous Words
Polysemy is a problem for methods that exploit image search engines to build object category models. Existing unsupervised approaches do not take word sense into consideration. We...
Kate Saenko, Trevor Darrell
KDD
2008
ACM
259views Data Mining» more  KDD 2008»
14 years 10 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, ...
LCN
2005
IEEE
14 years 3 months ago
Automated Traffic Classification and Application Identification using Machine Learning
The dynamic classification and identification of network applications responsible for network traffic flows offers substantial benefits to a number of key areas in IP network engi...
Sebastian Zander, Thuy T. T. Nguyen, Grenville J. ...