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13

ACL
2009

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Markov Random Topic Fields

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Markov Random Topic Fields

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Most approaches to topic modeling assume an independence between documents that is frequently violated. We present an topic model that makes use of one or more user-specified graphs describing relationships between documents. These graph are encoded in the form of a Markov random field over topics and serve to encourage related documents to have similar topic structures. Experiments on show upwards of a 10% improvement in modeling performance.

Hal Daume III

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ACL 2009 | Computational Linguistics | Markov Random Field | Similar Topic Structures | Topic Modeling Assume |

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Added	16 Feb 2011
Updated	16 Feb 2011
Type	Journal
Year	2009
Where	ACL
Authors	Hal Daume III

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