315 search results - page 1 / 63 » Text classification from positive and unlabeled documents |
CIKM
2003
Springer
13 years 10 months ago
2003
Springer
IJCAI
2003
13 years 6 months ago
2003
In traditional text classification, a classifier is built using labeled training documents of every class. This paper studies a different problem. Given a set P of documents of a ...
AMT
2006
Springer
13 years 8 months ago
2006
Springer
Text classification using positive and unlabeled data refers to the problem of building text classifier using positive documents (P) of one class and unlabeled documents (U) of man...
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...