Research Paper Summarization Using Extractive Approach
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-3242-5_17
Reference16 articles.
1. Yasunaga M, Kasai J, Zhang R, Fabbri AR, Li I, Friedman D, Radev DR (2019) ScisummNet: a large annotated corpus and content-impact models for scientific paper summarization with citation networks. arXiv preprint arXiv:1909.01716
2. Yu T, Su D, Dai W, Fung P (2020) Dimsum @LaySumm 20: BART-based approach for scientific document summarization, arXiv preprint arXiv:2010.09252
3. Xu H, Wang Z, Weng X (2019) Scientific literature summarization using document structure and hierarchical attention model. Proc IEEE
4. Cachola I, Lo K, Cohan A, Weld DS (2020) TLDR: extreme summarization of scientific documents. arXiv preprint arXiv:2004.15011
5. Ansary MdS (2021) A hybrid approach for automatic extractive summarization. In: Proceedings of international conference on information and communication technology for sustainable development (ICICT4SD)
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