Learning the Chinese Sentence Representation with LSTM Autoencoder

Author:

Chen Mu-Yen1,Huang Tien-Chi1,Shu Yu2,Chen Chia-Chen3,Hsieh Tsung-Che1,Yen Neil Y.4

Affiliation:

1. National Taichung University of Science and Technology, Taichung City, Taiwan Roc

2. National Changhua University of Education, Changhua City, Taiwan Roc

3. National Chung Hsing University, Taichung City, Taiwan Roc

4. University of Aizu, Aizu-Wakamatsu, Japan

Funder

Ministry of Science and Technology (Republic of China)

Publisher

ACM Press

Reference20 articles.

1. Q. Gan, B. H. Ferns, Y. Yu, & L. Jin. 2017. A text mining and multidimensional sentiment analysis of online restaurant reviews. Journal of Quality Assurance in Hospitality & Tourism, 18, 465--492.

2. S. M. Patel, V. K. Dabhi, & H. B. Prajapati. 2017. Extractive Based Automatic Text Summarization. JCP, 12, 550--563.

3. Q. Le, & T. Mikolov. 2014. Distributed representations of sentences and documents. In Proceedings of the 31st International Conference on Machine Learning, 1188--1196.

4. Y. Kim. 2014. Convolutional neural networks for sentence classification. arXiv preprint arXiv:1408.5882.

5. C. Dos Santos, & M. Gatti. 2014. Deep Convolutional Neural Networks for Sentiment Analysis of Short Texts. In COLING, 69--78.

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