Document Sentiment Classification based on the Word Embedding
- Yanping Yin, Zhong Jin
- Corresponding Author
- Yanping Yin
Available Online December 2015.
- https://doi.org/10.2991/icmmcce-15.2015.92How to use a DOI?
- Word Embedding; Support Vector Machine; Sentiment Classification
- 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.
- 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 -