Efficient Mind-Map Generation via Sequence-to-Graph and Reinforced Graph Refinement

Mengting Hu, Honglei Guo, Shiwan Zhao, Hang Gao, Zhong Su


Abstract
A mind-map is a diagram that represents the central concept and key ideas in a hierarchical way. Converting plain text into a mind-map will reveal its key semantic structure and be easier to understand. Given a document, the existing automatic mind-map generation method extracts the relationships of every sentence pair to generate the directed semantic graph for this document. The computation complexity increases exponentially with the length of the document. Moreover, it is difficult to capture the overall semantics. To deal with the above challenges, we propose an efficient mind-map generation network that converts a document into a graph via sequence-to-graph. To guarantee a meaningful mind-map, we design a graph refinement module to adjust the relation graph in a reinforcement learning manner. Extensive experimental results demonstrate that the proposed approach is more effective and efficient than the existing methods. The inference time is reduced by thousands of times compared with the existing methods. The case studies verify that the generated mind-maps better reveal the underlying semantic structures of the document.
Anthology ID:
2021.emnlp-main.641
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
8130–8141
Language:
URL:
https://aclanthology.org/2021.emnlp-main.641
DOI:
10.18653/v1/2021.emnlp-main.641
Bibkey:
Cite (ACL):
Mengting Hu, Honglei Guo, Shiwan Zhao, Hang Gao, and Zhong Su. 2021. Efficient Mind-Map Generation via Sequence-to-Graph and Reinforced Graph Refinement. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 8130–8141, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Efficient Mind-Map Generation via Sequence-to-Graph and Reinforced Graph Refinement (Hu et al., EMNLP 2021)
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PDF:
https://aclanthology.org/2021.emnlp-main.641.pdf
Video:
 https://aclanthology.org/2021.emnlp-main.641.mp4