Since we have a small seed set (5K words for English and 8K words for Bengali) and a large number of unlabeled words, we believe that it is most natural to apply a weakly supervised learning algorithm to bootstrap the clusters.
we employ a version of selftraining together with SVM as the underlying learning algorithm.