ML
2000
ACM
13 years 4 months ago
2000
ACM
This paper shows that the accuracy of learned text classifiers can be improved by augmenting a small number of labeled training documents with a large pool of unlabeled documents. ...
AAAI
1998
13 years 6 months ago
1998
In many important text classification problems, acquiring class labels for training documents is costly, while gathering large quantities of unlabeled data is cheap. This paper sh...
MLDM
2007
Springer
13 years 11 months ago
2007
Springer
This paper presents a novel solution for the problem of building text classifier using positive documents (P) and unlabeled documents (U). Here, the unlabeled documents are mixed w...
ICML
1998
IEEE
14 years 5 months ago
1998
IEEE
This paper shows how a text classifier's need for labeled training documents can be reduced by taking advantage of a large pool of unlabeled documents. We modify the Query-by...