In statistical machine translation, single-word based models have an important deficiency; they do not take contextual information into account for the translation decision. A poss...
This paper introduces a new discriminative learning technique for link prediction based on the matrix alignment approach. Our algorithm automatically determines the most predictiv...
Jerry Scripps, Pang-Ning Tan, Feilong Chen, Abdol-...
This paper presents an unsupervised approach to learning translation span alignments from parallel data that improves syntactic rule extraction by deleting spurious word alignment...
Abstract. Current numerical methods for assessing the statistical significance of local alignments with gaps are time consuming. Analytical solutions thus far have been limited to ...
For as long as biologists have been computing alignments of sequences, the question of what values to use for scoring substitutions and gaps has persisted. While some choices for s...