Voted Co-training for bootstrapping sense classifiers
Rada F. Mihalcea · European Conference on Artificial Intelligence · 2004
This paper introduces voted co-training, a bootstrapping method that combines co-training with majority voting, with the effect of smoothing the learning curves, and improving the average performance. Voted co-training was evaluated on a word sense classification problem, with significant improvements observed over basic co-training algorithms. Various empirical parameter selection methods for co-training are investigated, with various degrees of error reduction.