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Statistical natural language processing / Stochastic processes / Machine learning / Statistical models / Natural language processing / Latent Dirichlet allocation / Dirichlet process / Plate notation / Mixture model / Statistics / Probability and statistics / Probability


The Grouped Author-Topic Model for Unsupervised Entity Resolution Andrew M. Dai and Amos J. Storkey Institute for Adaptive and Neural Computation, School of Informatics, University of Edinburgh, U.K. {a.dai,a.storkey}@ed
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Document Date: 2011-09-27 08:11:22


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City

Morristown / Arlington / /

Company

Precision CiteSeer F1 / AUAI Press / Words Authors Group / Rexa Model / Amos J. Storkey Base Measures Group / Precision F1 Grouped A-T Group / DP / Andrew M. Dai / Baseline / Gelfand A.E. / /

Country

Jordan / United States / /

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Event

Product Issues / Product Recall / /

Facility

Amos J. Storkey Institute / University of Edinburgh / /

IndustryTerm

approximate algorithms / web search results / information extraction systems / Internet search engine / inferred / search engine / search results / Web People / /

MusicAlbum

U.K. / /

Organization

Amos J. Storkey Institute for Adaptive and Neural Computation / American Statistical Association / University of Edinburgh / Association for Computational Linguistics ACL / School of Informatics / Stanford / Association for Computational Linguistics / /

Person

Taylor J. Shawe / Amos J. Storkey / Andrew M. Dai / /

Position

author / global author / model / grouped author-topic model / group / author-topic model for authors and documents / Latent Dirichlet Model for Unsupervised Entity Resolution / co-author / particular author / /

Product

Precision CiteSeer F1 Recall Precision F1 Grouped A-T Group / /

ProvinceOrState

Virginia / /

PublishedMedium

Computational Linguistics / Journal of the American Statistical Association / /

Technology

Data Mining / search engine / machine learning / /

SocialTag