A Hybrid Framework for Text Modeling with Convolutional RNN-Reference-Cited by-同舟云学术

A Hybrid Framework for Text Modeling with Convolutional RNN

Published:2017-08-13 Issue: Volume: Page:
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Container-title:Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
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Author:

Wang Chenglong¹,Jiang Feijun¹,Yang Hongxia¹

Affiliation:

1. Alibaba Group, Hangzhou, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3097983.3098140

Reference52 articles.

1. K. Cho B.V. Merrienboer C. Gulcehre D. Bahdanau F. Bourgares H. Schwenk and Y. Bengio 2014. Learning phrase representations using rnn encoder-decoder for statistical machine translation. In arXiv preprint arXiv:1406.1078. K. Cho B.V. Merrienboer C. Gulcehre D. Bahdanau F. Bourgares H. Schwenk and Y. Bengio 2014. Learning phrase representations using rnn encoder-decoder for statistical machine translation. In arXiv preprint arXiv:1406.1078.

2. A M Dai and Q V. Le. 2015. Semi-Supervised Sequence Learning. In Advances in Neural Information Processing Systems. 3079--3087. A M Dai and Q V. Le. 2015. Semi-Supervised Sequence Learning. In Advances in Neural Information Processing Systems. 3079--3087.

3. A Statistical Parsing Framework for Sentiment Classification

4. M. Feng B. Xiang M.R. Glass L. Wang and B. Zhou 2015. Applying deep learning to answer selection: A study and an open task IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU). M. Feng B. Xiang M.R. Glass L. Wang and B. Zhou 2015. Applying deep learning to answer selection: A study and an open task IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU).

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