286 search results - page 17 / 58 » Learning to Classify Texts Using Positive and Unlabeled Data |
ASUNAM
2010
IEEE
13 years 10 months ago
2010
IEEE
The goal of semi-supervised learning (SSL) methods is to reduce the amount of labeled training data required by learning from both labeled and unlabeled instances. Macskassy and Pr...
CIKM
2009
Springer
14 years 3 months ago
2009
Springer
In this paper, we present a semi-supervised learning method for web page classification, leveraging click logs to augment training data by propagating class labels to unlabeled si...
ICPR
2008
IEEE
14 years 3 months ago
2008
IEEE
We propose a new transductive learning algorithm for learning optimal linear representations that utilizes unlabeled data. We pose the problem of learning linear representations a...
CIKM
2000
Springer
14 years 1 months ago
2000
Springer
Recently there has been significant interest in supervised learning algorithms that combine labeled and unlabeled data for text learning tasks. The co-training setting [1] applie...
ICML
2000
IEEE
14 years 9 months ago
2000
IEEE
This paper explores in detail the use of Error Correcting Output Coding (ECOC) for learning text classifiers. We show that the accuracy of a Naive Bayes Classifier over text class...