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IJCAI
2003
13 years 8 months ago
2003
We present a description of three different algorithms that use background knowledge to improve text classifiers. One uses the background knowledge as an index into the set of tra...
CASCON
2001
13 years 8 months ago
2001
The main problems in text classification are lack of labeled data, as well as the cost of labeling the unlabeled data. We address these problems by exploring co-training - an algo...
EMNLP
2010
13 years 5 months ago
2010
In this paper, we introduce a method that automatically builds text classifiers in a new language by training on already labeled data in another language. Our method transfers the...
AUSAI
2008
Springer
13 years 9 months ago
2008
Springer
Classifiers are traditionally learned using sets of positive and negative training examples. However, often a classifier is required, but for training only an incomplete set of pos...
DASFAA
2004
IEEE
13 years 11 months ago
2004
IEEE
Text classification using a small labeled set and a large unlabeled data is seen as a promising technique to reduce the labor-intensive and time consuming effort of labeling traini...