Automatic retrieval and clustering of similar words
Published 1 January 1998Open access
Dekang Lin
Citations1,555
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TL;DR
A word similarity measure based on the distributional pattern of words allows the automatically constructed thesaurus to be significantly closer to WordNet than Roget Thesaurus is.
Abstract
Bootstrapping semantics from text is one of the greatest challenges in natural language learning. We first define a word similarity measure based on the distributional pattern of words. The similarity measure allows us to construct a thesaurus using a parsed corpus. We then present a new evaluation methodology for the automatically constructed thesaurus. The evaluation results show that the thesaurus is significantly closer to WordNet than Roget Thesaurus is.
Keywords
Computer Science
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