Contemporary parser research is, to a large extent, focused on statistical parsers and deep-unification-based parsers. This paper describes an alternative, hybrid architecture in ...
The ability to distinguish statistically different populations of speakers or writers can be an important asset in many NLP applications. In this paper, we describe a method of us...
This paper presents an alternative algorithm based on the singular value decomposition (SVD) that creates vector representation for linguistic units with reduced dimensionality. T...
This paper presents two Markov chain Monte Carlo (MCMC) algorithms for Bayesian inference of probabilistic context free grammars (PCFGs) from terminal strings, providing an altern...
Mark Johnson, Thomas L. Griffiths, Sharon Goldwate...
Information retrieval systems are frequently required to handle long queries. Simply using all terms in the query or relying on the underlying retrieval model to appropriately wei...
We propose a method for extracting semantic orientations of phrases (pairs of an adjective and a noun): positive, negative, or neutral. Given an adjective, the semantic orientatio...
We present a revision learning model for improving the accuracy of a dependency parser. The revision stage corrects the output of the base parser by means of revision rules learne...
Previous multi-document relationship extraction and fusion research has focused on single relationships. Shifting the focus to multiple relationships allows for the use of mutual ...