Fast Concept Mention Grouping for Concept Map-based Multi-Document Summarization

Tobias Falke, Iryna Gurevych


Abstract
Concept map-based multi-document summarization has recently been proposed as a variant of the traditional summarization task with graph-structured summaries. As shown by previous work, the grouping of coreferent concept mentions across documents is a crucial subtask of it. However, while the current state-of-the-art method suggested a new grouping method that was shown to improve the summary quality, its use of pairwise comparisons leads to polynomial runtime complexity that prohibits the application to large document collections. In this paper, we propose two alternative grouping techniques based on locality sensitive hashing, approximate nearest neighbor search and a fast clustering algorithm. They exhibit linear and log-linear runtime complexity, making them much more scalable. We report experimental results that confirm the improved runtime behavior while also showing that the quality of the summary concept maps remains comparable.
Anthology ID:
N19-1074
Volume:
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
Month:
June
Year:
2019
Address:
Minneapolis, Minnesota
Editors:
Jill Burstein, Christy Doran, Thamar Solorio
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
695–700
Language:
URL:
https://aclanthology.org/N19-1074
DOI:
10.18653/v1/N19-1074
Bibkey:
Cite (ACL):
Tobias Falke and Iryna Gurevych. 2019. Fast Concept Mention Grouping for Concept Map-based Multi-Document Summarization. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), pages 695–700, Minneapolis, Minnesota. Association for Computational Linguistics.
Cite (Informal):
Fast Concept Mention Grouping for Concept Map-based Multi-Document Summarization (Falke & Gurevych, NAACL 2019)
Copy Citation:
PDF:
https://aclanthology.org/N19-1074.pdf
Video:
 https://aclanthology.org/N19-1074.mp4
Code
 UKPLab/naacl2019-cmaps-lshcw