Near-Synonym Choice in an Intelligent Thesaurus

An intelligent thesaurus assists a writer with alternative choices of words and orders them by their suitability in the writing context. In this paper we focus on methods for automatically choosing near-synonyms by their semantic coherence with the context. Our statistical method uses the Web as a corpus to compute mutual information scores. Evaluation experiments show that this method performs better than a previous method on the same task. We also propose and evaluate two more methods, one that uses anti-collocations, and one that uses supervised learning. To asses the difficulty of the task, we present results obtained by human judges.

• Type: Conference
• Year: 2007
• Where: NAACL
• Authors: Diana Zaiu Inkpen
• Keywords: Computational Linguistics, Intelligent Thesaurus, NAACL 2007, Semantic Coherence, Statistical Method