Jadhav, A and Rajan, V (2018) Extractive summarization with SWAP-Net: Sentences and words from alternating pointer networks. In: 56th Annual Meeting of the Association for Computational Linguistics, ACL 2018, 15 - 20 July 2018, Melbourne, pp. 142-151.
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Abstract
We present a new neural sequence-to-sequence model for extractive summarization called SWAP-NET (Sentences and Words from Alternating Pointer Networks). Extractive summaries comprising a salient subset of input sentences, often also contain important key words. Guided by this principle, we design SWAP-NET that models the interaction of key words and salient sentences using a new two-level pointer network based architecture. SWAP-NET identifies both salient sentences and key words in an input document, and then combines them to form the extractive summary. Experiments on large scale benchmark corpora demonstrate the efficacy of SWAP-NET that outperforms state-of-the-art extractive summarizers.
| Item Type: | Conference Paper |
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| Publication: | ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers) |
| Publisher: | Association for Computational Linguistics (ACL) |
| Additional Information: | The copyright for this article belongs to the Authors. |
| Keywords: | Extractive summarizations; Key words; Network-based architectures; Sequence modeling; State of the art, Computational linguistics |
| Department/Centre: | Division of Electrical Sciences > Electrical Engineering |
| Date Deposited: | 01 Sep 2022 10:20 |
| Last Modified: | 01 Sep 2022 10:20 |
| URI: | https://eprints.iisc.ac.in/id/eprint/76340 |
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