Elements of information theory
Elements of information theory
A training algorithm for optimal margin classifiers
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Representation and learning in information retrieval
Representation and learning in information retrieval
The nature of statistical learning theory
The nature of statistical learning theory
Transductive Inference for Text Classification using Support Vector Machines
ICML '99 Proceedings of the Sixteenth International Conference on Machine Learning
Information-theoretic co-clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Text classification by labeling words
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
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To reduce the human effort in labeling the training set for document classification, some learning algorithms ask users to give the representative keywords for each class rather than any labeled documents. The key challenge in such \emph {keyword-labeled classification} is how to learn the high quality classifier with very small number of keywords. In this paper, we propose a novel co-clustering based classification algorithm for keyword-labeled classification (CCKC) by utilizing auxiliary unlabeled documents. The experimental results show our algorithm greatly improves the classification performance over existing approaches.