Dynamic topic model

Results: 92



#Item
41RankTopic: Ranking Based Topic Modeling Dongsheng Duan† , Yuhua Li∗ † , Ruixuan Li† , Rui Zhang‡ and Aiming Wen† of Computer Science and Technology, Huazhong University of Science and Technology, China Email:

RankTopic: Ranking Based Topic Modeling Dongsheng Duan† , Yuhua Li∗ † , Ruixuan Li† , Rui Zhang‡ and Aiming Wen† of Computer Science and Technology, Huazhong University of Science and Technology, China Email:

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Source URL: www.ruizhang.info

Language: English - Date: 2012-10-11 20:49:56
42Learning Cross-modality Similarity for Multinomial Data Yangqing Jia UC Berkeley EECS Mathieu Salzmann TTI-Chicago

Learning Cross-modality Similarity for Multinomial Data Yangqing Jia UC Berkeley EECS Mathieu Salzmann TTI-Chicago

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Source URL: www.eecs.berkeley.edu

Language: English - Date: 2013-10-18 17:47:26
43David M. Blei Columbia University Department of Computer Science Department of Statistics Columbia University New York, NY

David M. Blei Columbia University Department of Computer Science Department of Statistics Columbia University New York, NY

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Source URL: www.cs.columbia.edu

Language: English - Date: 2014-10-27 10:16:43
44A Latent Variable Model for Geographic Lexical Variation Jacob Eisenstein Brendan O’Connor Noah A. Smith Eric P. Xing School of Computer Science Carnegie Mellon University

A Latent Variable Model for Geographic Lexical Variation Jacob Eisenstein Brendan O’Connor Noah A. Smith Eric P. Xing School of Computer Science Carnegie Mellon University

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Source URL: www.cs.cmu.edu

Language: English - Date: 2010-09-02 12:44:15
45Multiscale Topic Tomography Ramesh Nallapati William Cohen  Susan Ditmore

Multiscale Topic Tomography Ramesh Nallapati William Cohen Susan Ditmore

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Source URL: www.cs.cmu.edu

Language: English - Date: 2007-03-30 09:51:36
46Block-LDA: Jointly modeling entity-annotated text and entity-entity links William W. Cohen Machine Learning Department Carnegie Mellon University Pittsburgh, PA 15213

Block-LDA: Jointly modeling entity-annotated text and entity-entity links William W. Cohen Machine Learning Department Carnegie Mellon University Pittsburgh, PA 15213

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Source URL: www.cs.cmu.edu

Language: English - Date: 2011-01-03 11:15:42
47Dynamic Topic Adaptation for Phrase-based MT Eva Hasler1 , Phil Blunsom2 , Philipp Koehn1 , Barry Haddow1 1 School of Informatics, University of Edinburgh 2 Dept. of Computer Science, University of Oxford  Abstract

Dynamic Topic Adaptation for Phrase-based MT Eva Hasler1 , Phil Blunsom2 , Philipp Koehn1 , Barry Haddow1 1 School of Informatics, University of Edinburgh 2 Dept. of Computer Science, University of Oxford Abstract

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Source URL: aclweb.org

Language: English - Date: 2014-04-18 06:11:01
48Latent Dirichlet allocation / Dynamic topic model / Topic model / Mixture model / Dirichlet distribution / Multinomial distribution / Statistics / Statistical natural language processing / Probability and statistics

Continuous Time Group Discovery in Dynamic Graphs Tina Eliassi-Rad2 [removed]

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Source URL: snap.stanford.edu

Language: English - Date: 2009-11-25 18:32:54
49Link-PLSA-LDA: A new unsupervised model for topics and influence of blogs Ramesh Nallapati and William Cohen {[removed]} {[removed]} Machine Learning Department, Carnegie Mellon University,

Link-PLSA-LDA: A new unsupervised model for topics and influence of blogs Ramesh Nallapati and William Cohen {[removed]} {[removed]} Machine Learning Department, Carnegie Mellon University,

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Source URL: www.cs.cmu.edu

Language: English - Date: 2008-02-18 10:45:33
50From Topic Models to Semi-Supervised Learning: Biasing Mixed-membership Models to Exploit Topic-Indicative Features in Entity Clustering Ramnath Balasubramanyan1 , Bhavana Dalvi1 , and William W. Cohen1,2 {rbalasub,bbd,w

From Topic Models to Semi-Supervised Learning: Biasing Mixed-membership Models to Exploit Topic-Indicative Features in Entity Clustering Ramnath Balasubramanyan1 , Bhavana Dalvi1 , and William W. Cohen1,2 {rbalasub,bbd,w

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Source URL: www.cs.cmu.edu

Language: English - Date: 2013-07-01 09:45:45