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• W201532657 abstract "This work presents an algorithm for the unsupervised learning, or induction, of a simple morphology of a natural language. A probabilistic maximum a posteriori model is utilized, which builds hierarchical representations for a set of morphs, which are morpheme-like units discovered from unannotated text corpora. The induced morph lexicon stores parameters related to both the “meaning” and “form” of the morphs it contains. These parameters affect the role of the morphs in words. The model is implemented in a task of unsupervised morpheme segmentation of Finnish and English words. Very good results are obtained for Finnish and almost as good results are obtained in the English task." @default.
• W201532657 created "2016-06-24" @default.
• W201532657 creator A5025714966 @default.
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• W201532657 date "2005-01-01" @default.
• W201532657 modified "2023-09-30" @default.
• W201532657 title "INDUCING THE MORPHOLOGICAL LEXICON OF A NATURAL LANGUAGE FROM UNANNOTATED TEXT" @default.
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