Deep hierarchical encoding model for sentence semantic matching-Reference-Cited by-同舟云学术

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Deep hierarchical encoding model for sentence semantic matching

Published:2020-08 Issue: Volume:71 Page:102794
ISSN:1047-3203
Container-title:Journal of Visual Communication and Image Representation
language:en
Short-container-title:Journal of Visual Communication and Image Representation

Author:

Lu Wenpeng,Zhang Xu^ORCID,Lu Huimin^ORCID,Li Fangfang

Funder

National Nature Science Foundation of China

National Key Research and Development Program of China

Taishan Scholar Program of Shandong Province in China

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Media Technology,Signal Processing

Reference49 articles.

1. C. Duan, L. Cui, X. Chen, F. Wei, C. Zhu, T. Zhao, Attention-fused deep matching network for natural language inference, in: Proceedings of the 27th International Joint Conference on Artificial Intelligence, 2018, pp. 4033–4040.

2. J. Chen, Q. Chen, X. Liu, H. Yang, D. Lu, B. Tang, The bq corpus: a large-scale domain-specific chinese corpus for sentence semantic equivalence identification, in: Proceedings of the Conference on Empirical Methods in Natural Language Processing, 2018, pp. 4946–4951.

3. Chinese medical question answer selection via hybrid models based on CNN and GRU;Zhang;Multimed. Tools Appl.,2019

4. L. Xia, J. Xu, Y. Lan, J. Guo, X. Cheng, Modeling document novelty with neural tensor network for search result diversification, in: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016, pp. 395–404.

5. B. Mitra, F. Diaz, N. Craswell, Learning to match using local and distributed representations of text for web search, in: Proceedings of the 26th International Conference on World Wide Web, 2017, pp. 1291–1299.

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