Automatic sentiment classification of product reviews.
This dissertation reports a study in automatic sentiment classification, i.e. automatically classifying documents as expressing positive or negative sentiments.
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2008
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Online Access: | http://hdl.handle.net/10356/2094 |
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sg-ntu-dr.10356-20942019-12-10T14:01:18Z Automatic sentiment classification of product reviews. Zhou, Yun Yun. Na, Jin Cheon Wee Kim Wee School of Communication and Information Khoo, Christopher Soo Guan DRNTU::Engineering::Computer science and engineering::Computing methodologies::Document and text processing This dissertation reports a study in automatic sentiment classification, i.e. automatically classifying documents as expressing positive or negative sentiments. Master of Science (Information Studies) 2008-09-10T08:39:15Z 2008-09-10T08:39:15Z 2004 2004 Thesis http://hdl.handle.net/10356/2094 Nanyang Technological University application/pdf |
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DRNTU::Engineering::Computer science and engineering::Computing methodologies::Document and text processing |
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DRNTU::Engineering::Computer science and engineering::Computing methodologies::Document and text processing Zhou, Yun Yun. Automatic sentiment classification of product reviews. |
description |
This dissertation reports a study in automatic sentiment classification, i.e. automatically classifying documents as expressing positive or negative sentiments. |
author2 |
Na, Jin Cheon |
author_facet |
Na, Jin Cheon Zhou, Yun Yun. |
format |
Theses and Dissertations |
author |
Zhou, Yun Yun. |
author_sort |
Zhou, Yun Yun. |
title |
Automatic sentiment classification of product reviews. |
title_short |
Automatic sentiment classification of product reviews. |
title_full |
Automatic sentiment classification of product reviews. |
title_fullStr |
Automatic sentiment classification of product reviews. |
title_full_unstemmed |
Automatic sentiment classification of product reviews. |
title_sort |
automatic sentiment classification of product reviews. |
publishDate |
2008 |
url |
http://hdl.handle.net/10356/2094 |
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1681048080899637248 |