An algorithm for the unsupervised learning of morphology
Natural Language EngineeringPublished 10 January 2006
John Goldsmith
Citations144
SJR quartileQ1
SJR score0.64
SNIP1.66
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TL;DR
This paper describes in detail an algorithm for the unsupervised learning of natural language morphology, with emphasis on challenges that are encountered in languages typologically similar to European languages.
Abstract
This paper describes in detail an algorithm for the unsupervised learning of natural language morphology, with emphasis on challenges that are encountered in languages typologically similar to European languages. It utilizes the Minimum Description Length analysis described in Goldsmith (2001), and has been implemented in software that is available for downloading and testing.
Keywords
Computer Science
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