Multi-Document Scientific Summarization from a Knowledge Graph-Centric View
Pancheng Wang, Shasha Li, Kunyuan Pang, Liangliang He, Dong Li, Jintao Tang, Ting Wang
Abstract
Multi-Document Scientific Summarization (MDSS) aims to produce coherent and concise summaries for clusters of topic-relevant scientific papers. This task requires precise understanding of paper content and accurate modeling of cross-paper relationships. Knowledge graphs convey compact and interpretable structured information for documents, which makes them ideal for content modeling and relationship modeling. In this paper, we present KGSum, an MDSS model centred on knowledge graphs during both the encoding and decoding process. Specifically, in the encoding process, two graph-based modules are proposed to incorporate knowledge graph information into paper encoding, while in the decoding process, we propose a two-stage decoder by first generating knowledge graph information of summary in the form of descriptive sentences, followed by generating the final summary. Empirical results show that the proposed architecture brings substantial improvements over baselines on the Multi-Xscience dataset.- Anthology ID:
- 2022.coling-1.543
- Volume:
- Proceedings of the 29th International Conference on Computational Linguistics
- Month:
- October
- Year:
- 2022
- Address:
- Gyeongju, Republic of Korea
- Editors:
- Nicoletta Calzolari, Chu-Ren Huang, Hansaem Kim, James Pustejovsky, Leo Wanner, Key-Sun Choi, Pum-Mo Ryu, Hsin-Hsi Chen, Lucia Donatelli, Heng Ji, Sadao Kurohashi, Patrizia Paggio, Nianwen Xue, Seokhwan Kim, Younggyun Hahm, Zhong He, Tony Kyungil Lee, Enrico Santus, Francis Bond, Seung-Hoon Na
- Venue:
- COLING
- SIG:
- Publisher:
- International Committee on Computational Linguistics
- Note:
- Pages:
- 6222–6233
- Language:
- URL:
- https://aclanthology.org/2022.coling-1.543
- DOI:
- Cite (ACL):
- Pancheng Wang, Shasha Li, Kunyuan Pang, Liangliang He, Dong Li, Jintao Tang, and Ting Wang. 2022. Multi-Document Scientific Summarization from a Knowledge Graph-Centric View. In Proceedings of the 29th International Conference on Computational Linguistics, pages 6222–6233, Gyeongju, Republic of Korea. International Committee on Computational Linguistics.
- Cite (Informal):
- Multi-Document Scientific Summarization from a Knowledge Graph-Centric View (Wang et al., COLING 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2022.coling-1.543.pdf
- Code
- muguruzawang/kgsum