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POS induction with distributional and morphological information using a distance-dependent Chinese Restaurant Process
Sirts, Kairit; Eisenstein, Jacob; Elsner, Micha; Goldwater, Sharon. - : Stroudsburg, PA : Association for Computational Linguistics, 2014
Abstract: We present a new approach to inducing the syntactic categories of words, combining their distributional and morphological properties in a joint nonparametric Bayesian model based on the distance-dependent Chinese Restaurant Process. The prior distribution over word clusterings uses a log-linear model of morphological similarity; the likelihood function is the probability of generating vector word embeddings. The weights of the morphology model are learned jointly while inducing part-of-speech clusters, encouraging them to cohere with the distributional features. The resulting algorithm outperforms competitive alternatives on English POS induction. ; 7 page(s)
Keyword: 080100 Artificial Intelligence and Image Processing; 200400 Linguistics
URL: http://hdl.handle.net/1959.14/1044108
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