Selecting the “Right” Number of Senses Based on Clustering Criterion Functions

This paper describes an unsupervised knowledge-lean methodology for automatically determining the number of senses in which an ambiguous word is used in a large corpus. It is based on the use of global criterion functions that assess the quality of a clustering solution.

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