Hierarchical Attentional Hybrid Neural Networks for Document Classification-Reference-Cited by-同舟云学术

Hierarchical Attentional Hybrid Neural Networks for Document Classification

Published:2019 Issue: Volume: Page:396-402
ISSN:0302-9743
Container-title:Artificial Neural Networks and Machine Learning – ICANN 2019: Workshop and Special Sessions
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Author:

Abreu Jader^ORCID,Fred Luis^ORCID,Macêdo David^ORCID,Zanchettin Cleber^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-30493-5_39

Reference7 articles.

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2. Bai, S., Kolter, J.Z., Koltun, V.: An empirical evaluation of generic convolutional and recurrent networks for sequence modeling. arXiv preprint arXiv:1803.01271 (2018)

3. Bojanowski, P., et al.: Enriching word vectors with subword information. arXiv preprint arXiv:1607.04606 (2016). https://doi.org/10.1162/tacl_a_00051

4. Cho, K., et al.: Learning phrase representations using RNN encoder-decoder for statistical machine translation. arXiv preprint arXiv:1406.1078 (2014). https://doi.org/10.3115/v1/D14-1179

5. Kim, Y.: Convolutional neural networks for sentence classification. arXiv preprint arXiv:1408.5882 (2014). https://doi.org/10.3115/v1/D14-1181

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