133 citations · 478 across the 17 of their papers we have counts for
5 papers · 1 filter
Distinguishing Word Senses in Untagged Text
Ted Pedersen, Rebecca Bruce
This paper describes an experimental comparison of three unsupervised learning algorithms that distinguish the sense of an ambiguous word in untagged text. The methods described in…
Sequential Model Selection for Word Sense Disambiguation
Ted Pedersen, Rebecca Bruce, Janyce Wiebe
Statistical models of word-sense disambiguation are often based on a small number of contextual features or on a model that is assumed to characterize the interactions among a set…
Fishing for Exactness
Ted Pedersen
Statistical methods for automatically identifying dependent word pairs (i.e. dependent bigrams) in a corpus of natural language text have traditionally been performed using asympto…
The Measure of a Model
Rebecca Bruce, Janyce Wiebe, Ted Pedersen
This paper describes measures for evaluating the three determinants of how well a probabilistic classifier performs on a given test set. These determinants are the appropriateness,…
Lexical Acquisition via Constraint Solving
Ted Pedersen, Weidong Chen
This paper describes a method to automatically acquire the syntactic and semantic classifications of unknown words. Our method reduces the search space of the lexical acquisition p…