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» Sampling the Web as Training Data for Text Classification
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JIFS
2008
155views more  JIFS 2008»
15 years 3 months ago
Improving supervised learning performance by using fuzzy clustering method to select training data
The crucial issue in many classification applications is how to achieve the best possible classifier with a limited number of labeled data for training. Training data selection is ...
Donghai Guan, Weiwei Yuan, Young-Koo Lee, Andrey G...
CHI
2004
ACM
16 years 3 months ago
Acquiring in situ training data for context-aware ubiquitous computing applications
Ubiquitous, context-aware computer systems may ultimately enable computer applications that naturally and usefully respond to a user's everyday activity. Although new algorit...
Stephen S. Intille, Ling Bao, Emmanuel Munguia Tap...
AUSAI
2008
Springer
15 years 4 months ago
Cross-Domain Knowledge Transfer Using Semi-supervised Classification
Traditional text classification algorithms are based on a basic assumption: the training and test data should hold the same distribution. However, this identical distribution assum...
Yi Zhen, Chunping Li
MM
2005
ACM
143views Multimedia» more  MM 2005»
15 years 8 months ago
Hierarchical voting classification scheme for improving visual sign language recognition
As one of the important research areas of multimodal interaction, sign language recognition (SLR) has attracted increasing interest. In SLR, especially on medium or large vocabula...
Liang-Guo Zhang, Xilin Chen, Chunli Wang, Wen Gao
ICML
2005
IEEE
16 years 3 months ago
A model for handling approximate, noisy or incomplete labeling in text classification
We introduce a Bayesian model, BayesANIL, that is capable of estimating uncertainties associated with the labeling process. Given a labeled or partially labeled training corpus of...
Ganesh Ramakrishnan, Krishna Prasad Chitrapura, Ra...