Using RST-based deep neural networks to improve text representation

Author:

Gharavi Erfaneh,Veisi Hadi

Publisher

Apex Publishing

Reference36 articles.

1. [1] R. Socher, C. D. C. Manning, and A. Y. A. Ng, "Learning continuous phrase representations and syntactic parsing with recursive neural networks," Proc. NIPS-2010 Deep Learn. Unsupervised Featur. Learn. Work., pp. 1-9, 2010.

2. [2] R. Socher, C. Manning, B. Huval, and A. Ng, "Semantic compositionality through recursive matrix-vector spaces," in EMNLP-CoNLL '12: Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning, 2012, pp. 1201-1211.

3. [3] Y. Bengio, R. Ducharme, P. Vincent, and C. Janvin, "A Neural Probabilistic Language Model," J. Mach. Learn. Res., vol. 3, pp. 1137-1155, 2003.

4. Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks

5. A Convolutional Neural Network for Modelling Sentences

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