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A Bayesian LDA-based model for semi-supervised part-of-speech tagging
Kristina N Toutanova · Mark Johnson

Mon Dec 03 08:10 PM -- 08:25 PM (PST) @ None

We present a novel Bayesian statistical model for semi-supervised part-of-speech tagging. Our model extends the Latent Dirichlet Allocation (LDA) model and incorporates the intuition that words' distributions over tags, p(t|w), are sparse. In addition we introduce a model for determining the set of possible tags of a word which captures important dependencies in the ambiguity classes of words. Our model outperforms the best previously proposed model for this task on a standard dataset.

Author Information

Kristina N Toutanova (Microsoft Research)
Mark Johnson (Macquarie University)

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