A Comparison of Statistical Models for the Extraction of Lexical Information from Text Corpor
Year: 2003
Type: article
Abstract: The Syntagmatic Paradigmatic model (SP; Dennis & Harrington 2001, Dennis submitted) and the Pooled Adjacent Context model (PAC; Redington, Chater & Finch 1998) are compared on their ability to extract syntactic, semantic and associative information from a corpus of text.On a measure of syntactic class (and subclass) information based on the WordNet lexical database (Miller 1990), the models performed similarly with a small advantage for the PAC model.On a measure of semantic structure based on the similarities produced by Latent Semantic Analysis (LSA; Landauer & Dumais 1997), the models performed equivalently with a small advantage for the SP model.On a measure of associative information based on the free association norms of Nelson, McEvoy & Schreiber (1999), the SP model shows a substantive advantage over the PAC model producing more than twice as many associates.
Author: Simon Dennis
Institution: University of Colorado Boulder
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Funder: National Science Foundation
OpenAlex ID: W189189005