Motivated by Google Sets, we study the problem of growing related words from a single seed word by leveraging user behaviors hiding in user records of Chinese input method. Our pr...
Recently, relaxation approaches have been successfully used for MAP inference on NLP problems. In this work we show how to extend the relaxation approach to marginal inference use...
This paper presents a direct word reordering model with novel syntax-based features for statistical machine translation. Reordering models address the problem of reordering source...
Out-of-vocabulary (OOV) words represent an important source of error in large vocabulary continuous speech recognition (LVCSR) systems. These words cause recognition failures, whi...
Carolina Parada, Mark Dredze, Denis Filimonov, Fre...
Open-class semantic lexicon induction is of great interest for current knowledge harvesting algorithms. We propose a general framework that uses patterns in bootstrapping fashion ...