Integrating Topics and Syntax

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Integrating Topics and Syntax
Statistical approaches to language learning typically focus on either short-range syntactic dependencies or long-range semantic dependencies between words. We present a generative model that uses both kinds of dependencies, and can be used to simultaneously find syntactic classes and semantic topics despite having no representation of syntax or semantics beyond statistical dependency. This model is competitive on tasks like part-of-speech tagging and document classification with models that exclusively use short- and long-range dependencies respectively.
Thomas L. Griffiths, Mark Steyvers, David M. Blei,
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where NIPS
Authors Thomas L. Griffiths, Mark Steyvers, David M. Blei, Joshua B. Tenenbaum
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