Yuan, Q;
Ni, P;
Liu, J;
Tong, X;
Lu, H;
Li, G;
Guan, S;
(2021)
An Encoder-decoder Architecture with Graph Convolutional Networks for Abstractive Summarization.
In:
2021 IEEE 4th International Conference on Big Data and Artificial Intelligence, BDAI 2021.
(pp. pp. 91-97).
IEEE: Qingdao, China.
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Abstract
We propose a single-document abstractive summarization system that integrates token relation into a traditional RNN-based encoder-decoder architecture. We employ pointer-wise mutual information to represent the token relation and adopt Graph Convolutional Networks (GCN) to extract token representation from the relation graph. In our experiment on Gigaword, we consider importing two kinds of structural information: token (node) representation from the relation graph. Also, we implement two kinds of GCNs, a spectral-based one and a spatial-based one, to extract structural information. The result shows that the spatial based GCN-enhanced model with node representation outperforms the classical RNN-based encoder-decoder model.
| Type: | Proceedings paper |
|---|---|
| Title: | An Encoder-decoder Architecture with Graph Convolutional Networks for Abstractive Summarization |
| Event: | 2021 IEEE 4th International Conference on Big Data and Artificial Intelligence (BDAI) |
| Dates: | 2 Jul 2021 - 4 Jul 2021 |
| ISBN-13: | 9781665412704 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/BDAI52447.2021.9515256 |
| Publisher version: | https://doi.org/10.1109/BDAI52447.2021.9515256 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Architecture, Conferences, Buildings, Big Data, Data models, Data mining, Artificial intelligence |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10159889 |
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