Unlabeled data sets
1Scaling Semi-supervised Naive Bayes with Feature Marginalssemi-supervised text classification that scales to massive unlabeled data sets. We present a novel learning algorithm, which optimizes...
2Word Translation Disambiguation Using Bilingual BootstrappingMB-B classifiers constructed with two different unlabeled data sets and we found that although the accuracies get some...
4A High-Performance Semi-Supervised Learning Method for Text Chunkingthe official training/development/test splits. Our unlabeled data sets consist of 27 million words (English) and 35 million...
5Active Learning for Multilingual Statistical Machine Translationfor generating phrases in each of the labeled and unlabeled data sets. To generate a phrase, we first toss a coin and depending...