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Learning / Semi-supervised learning / Transduction / Supervised learning / Support vector machine / Unsupervised learning / Graph / Machine learning / Artificial intelligence / Statistics


Seeing stars when there aren’t many stars: Graph-based semi-supervised learning for sentiment categorization Andrew B. Goldberg
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Document Date: 2006-04-24 10:49:53

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City

Dordrecht / Bonn / /

Company

MIT Press / Computer Sciences / ACM Press / /

Country

Germany / Netherlands / /

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Facility

Xiaojin Zhu Computer Sciences Department University of Wisconsin-Madison Madison / University of Edinburgh / Andrew B. Goldberg Computer Sciences Department University of Wisconsin-Madison Madison / University of Wisconsin-Madison / /

IndustryTerm

graph-based semi-supervised learning algorithm / data mining / supervised machine learning algorithms / energy / Movie review mining / consumer product / metric labeling algorithm / closed-form solution / tion algorithms / learning algorithm / learning algorithms / /

Organization

MIT / University of Edinburgh / IEEE Computer Society / University of Wisconsin / Association for Computational Linguistics / /

Person

Mikhail Belkin / Xiaojin Zhu / Partha Niyogi / Pimwadee Chaovalit / Pang / John Lafferty / Bing Liu / Vikas Sindhwani / Minqing Hu / Bo Pang / Zoubin Ghahramani / Yan Qu / Janyce Wiebe / James Shanahan / Lillian Lee / Matthias Seeger / Lina Zhou / Peter Turney / David M. Pennock / Nicolas Le Roux / Yoshua Bengio / Olivier Delalleau / Steve Lawrence / Kushal Dave / /

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Position

critic / author / /

ProvinceOrState

Wisconsin / /

PublishedMedium

Computational Linguistics / Machine Learning / /

Technology

graph-based semi-supervised learning algorithm / Supervised learning algorithms / Eva tion algorithms / supervised machine learning algorithms / machine learning / SSL / pdf / SSL algorithm / artificial intelligence / metric labeling algorithm / data mining / SSL+PSP algorithm / five algorithms / /

URL

rottentomatoes.com / http /

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