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» Intelligent Selection of Language Model Training Data
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WWW
2005
ACM
16 years 5 months ago
Hybrid semantic tagging for information extraction
The semantic web is expected to have an impact at least as big as that of the existing HTML based web, if not greater. However, the challenge lays in creating this semantic web an...
Ronen Feldman, Binyamin Rosenfeld, Moshe Fresko, B...
131
Voted
AAAI
2010
15 years 6 months ago
G-Optimal Design with Laplacian Regularization
In many real world applications, labeled data are usually expensive to get, while there may be a large amount of unlabeled data. To reduce the labeling cost, active learning attem...
Chun Chen, Zhengguang Chen, Jiajun Bu, Can Wang, L...
FLAIRS
2008
15 years 7 months ago
Building Useful Models from Imbalanced Data with Sampling and Boosting
Building useful classification models can be a challenging endeavor, especially when training data is imbalanced. Class imbalance presents a problem when traditional classificatio...
Chris Seiffert, Taghi M. Khoshgoftaar, Jason Van H...
ICCV
2003
IEEE
16 years 6 months ago
Automatically Labeling Video Data Using Multi-class Active Learning
Labeling video data is an essential prerequisite for many vision applications that depend on training data, such as visual information retrieval, object recognition, and human act...
Rong Yan, Jie Yang, Alexander G. Hauptmann
142
Voted
NAACL
2010
15 years 2 months ago
Improved Extraction Assessment through Better Language Models
A variety of information extraction techniques rely on the fact that instances of the same relation are "distributionally similar," in that they tend to appear in simila...
Arun Ahuja, Doug Downey