Hierarchical bayesian modeling of topics in time-stamped documents
We consider the problem of inferring and modeling topics in a sequence of documents with known publication dates. The documents at a given time are each characterized by a topic and the topics are drawn from a mixture model. The proposed model infers the change in the topic mixture weights as a func...
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Détails bibliographiques
| Publié dans: | IEEE transactions on pattern analysis and machine intelligence. - 1998. - 32(2010), 6 vom: 02. Juni, Seite 996-1011
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| Auteur principal: |
Pruteanu-Malinici, Iulian
(Auteur) |
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| Autres auteurs: |
Ren, Lu,
Paisley, John,
Wang, Eric,
Carin, Lawrence |
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| Format: | Article en ligne
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| Langue: | English |
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| Publié: |
2010
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| Accès à la collection: | IEEE transactions on pattern analysis and machine intelligence
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| Sujets: | Journal Article |
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