Abstract
Current evaluation metrics for timeline summarization either ignore the temporal aspect of the task or require strict date matching. We introduce variants of ROUGE that allow alignment of daily summaries via temporal distance or semantic similarity. We argue for the suitability of these variants in a theoretical analysis and demonstrate it in a battery of task-specific tests.- Anthology ID:
- E17-2046
- Volume:
- Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers
- Month:
- April
- Year:
- 2017
- Address:
- Valencia, Spain
- Editors:
- Mirella Lapata, Phil Blunsom, Alexander Koller
- Venue:
- EACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 285–290
- Language:
- URL:
- https://aclanthology.org/E17-2046
- DOI:
- Cite (ACL):
- Sebastian Martschat and Katja Markert. 2017. Improving ROUGE for Timeline Summarization. In Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers, pages 285–290, Valencia, Spain. Association for Computational Linguistics.
- Cite (Informal):
- Improving ROUGE for Timeline Summarization (Martschat & Markert, EACL 2017)
- PDF:
- https://preview.aclanthology.org/proper-vol2-ingestion/E17-2046.pdf