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 thesaurns is significantly closer to WordNet than Roget Thesaurus is.
REF constructed a thesaurus by automatically clustering words based on context similarity.
Automatic Retrieval and Clustering of Similar Words
COLING-ACL
Computer Science