125 search results - page 1 / 25 » Combining labeled and unlabeled data with word-class distrib... |
CIKM
2009
Springer
15 years 7 months ago
2009
Springer
We describe a novel simple and highly scalable semi-supervised method called Word-Class Distribution Learning (WCDL), and apply it the task of information extraction (IE) by utili...
102
Voted
IJCNLP
2004
Springer
15 years 5 months ago
2004
Springer
Multi-document discourse analysis has emerged with the potential of improving various NLP applications. Based on the newly proposed Cross-document Structure Theory (CST), this pap...
100
Voted
ICML
2002
IEEE
16 years 1 months ago
2002
IEEE
Supervised learning techniques for text classi cation often require a large number of labeled examples to learn accurately. One way to reduce the amountoflabeled datarequired is t...
COLT
2005
Springer
15 years 6 months ago
2005
Springer
Abstract. There has been growing interest in practice in using unlabeled data together with labeled data in machine learning, and a number of different approaches have been develo...
118
Voted
KDD
2002
ACM
16 years 25 days ago
2002
ACM
In this paper, we present a new co-training strategy that makes use of unlabelled data. It trains two predictors in parallel, with each predictor labelling the unlabelled data for...