Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015

Document Sentiment Classification based on the Word Embedding

Authors
Yanping Yin, Zhong Jin
Corresponding Author
Yanping Yin
Available Online December 2015.
DOI
https://doi.org/10.2991/icmmcce-15.2015.92How to use a DOI?
Keywords
Word Embedding; Support Vector Machine; Sentiment Classification
Abstract
N-gram feature is commonly used to represent document, however, it often leads to the curse of dimensionality. Sentiment classification based on word embedding and SVM is proposed. The method uses word embedding to represent document, which can make the final representation of the document consistent with the dimension of word embedding. Experiments show that the proposed method can significant reduce the dimension of document representation and improve the accuracy of document sentiment classification.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
2015 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering
Part of series
Advances in Computer Science Research
Publication Date
December 2015
ISBN
978-94-6252-133-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmmcce-15.2015.92How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Yanping Yin
AU  - Zhong Jin
PY  - 2015/12
DA  - 2015/12
TI  - Document Sentiment Classification based on the Word Embedding
BT  - 2015 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.92
DO  - https://doi.org/10.2991/icmmcce-15.2015.92
ID  - Yin2015/12
ER  -