A Novel Sentence Vector Generation Method Based on Autoencoder and Bi-directional LSTM

Author:

Fukuda Kiyohito,Mori Naoki,Matsumoto Keinosuke

Publisher

Springer International Publishing

Reference14 articles.

1. Pennington, J., Socher, R., Manning, C.D.: Glove: global vectors for word representation. In: EMNLP, vol. 14, pp. 1532–1543 (2014)

2. Vinyals, O., Toshev, A., Bengio, S., Erhan, D.: Show and tell: a neural image caption generator. In: Computer Vision and Pattern Recognition (2015)

3. Mikolov, T., Chen, K., Corrado, G., Dean, J.: Efficient estimation of word representations in vector space. CoRR, abs/1301.3781 (2013)

4. Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distributed representations of words and phrases and their compositionality. In: Burges, C.J.C., Bottou, L., Welling, M., Ghahramani, Z., Weinberger, K.Q. (eds.) Advances in Neural Information Processing Systems, vol. 26, pp. 3111–3119. Curran Associates, Inc. (2013)

5. Logeswaran, L., Lee, H.: An efficient framework for learning sentence representations. In: International Conference on Learning Representations (2018)

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