We investigate full-scale shortest-derivation parsing (SDP), wherein the parser selects an analysis built from the fewest number of training fragments. Shortest derivation parsing...
We investigate the problem of determining the polarity of sentiments when one or more occurrences of a negation term such as “not” appear in a sentence. The concept of the sco...
When translating among languages that differ substantially in word order, machine translation (MT) systems benefit from syntactic preordering—an approach that uses features fro...
We introduce a novel training algorithm for unsupervised grammar induction, called Zoomed Learning. Given a training set T and a test set S, the goal of our algorithm is to identi...
This paper proposes a general probabilistic framework for shape-based modeling and classification of waveform data. A segmental hidden Markov model (HMM) is used to characterize w...