Automatic text summarization for government news reports based on multiple features-Reference-Cited by-同舟云学术

Automatic text summarization for government news reports based on multiple features

Published:2023-08-30 Issue:3 Volume:80 Page:3212-3228
ISSN:0920-8542
Container-title:The Journal of Supercomputing
language:en
Short-container-title:J Supercomput

Author:

Yang Yanni,Tan Yiting,Min Jintao,Huang Zhengwei

Funder

The National Social Science Fund of China

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Information Systems,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s11227-023-05599-0.pdf

Reference25 articles.

1. China Internet Network Information Center (2022) 49th Statistical Report. The 49th Statistical Report on China’s Internet Development. http://www.cnnic.net.cn/n4/2022/0401/c88-1131.html

2. Gambhir M, Gupta V (2017) Recent automatic text summarization techniques: a survey. Artif Intell Rev 47(1):1–66

3. Nallapati R, Zhou B, Santos C, Gulcehre, Xiang B (2016) Abstractive text summarization using sequence-to-sequence RNNs and beyond. In: Proceedings of the 20th SIGNLL Conference on Computational Natural Language Learning, pp 280–290

4. Blei D, Ng A, Jordan M (2013) Latent dirichlet allocation. J Mach Learn Res 3:993–1022

5. Hofmann T (2017) Probabilistic latent semantic indexing. ACM SIGIR Forum 51(2):211–218

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