This paper suggests the efficient indexing method based on a concept vector space that is capable of representing the semantic content of a document. The two information measure,...
In this paper, we propose a machine learning algorithm for shallow semantic parsing, extending the work of Gildea and Jurafsky (2002), Surdeanu et al. (2003) and others. Our algor...
Sameer Pradhan, Wayne Ward, Kadri Hacioglu, James ...
We propose a set of metrics for measuring the semantic implications of changes during ontology evolution. Our metrics focus on the changes of classes and associated axioms or annot...
In this paper, we present a method for the semantic tagging of word chunks extracted from a written transcription of conversations. This work is part of an ongoing project for an ...
Lexical selection is a significant problem for widecoverage machine translation: depending on the context, a given source language word can often be translated into different targ...