Several recent efforts in statistical natural language understanding (NLU) have focused on generating clumps of English words from semantic meaning concepts (Miller et al., 1995; ...
Stephen Della Pietra, Mark Epstein, Salim Roukos, ...
We present a probabilistic generative model for learning semantic parsers from ambiguous supervision. Our approach learns from natural language sentences paired with world states ...
We propose to model the development of language by a series of formal grammars, accounting for the linguistic capacity of children at the very early stages of mastering language. T...
The Semantic Web, also known as the Web of meaning, is considered the new generation of the Web. Its objective is to enable computers and people to work in cooperation. A requisit...
In this paper we propose a probabilistic model for online document clustering. We use non-parametric Dirichlet process prior to model the growing number of clusters, and use a pri...