Abstract
This paper proposes an extractive multi-document summarization approach based on an ant colony system to optimize the information coverage of summary sentences. The implemented system was evaluated on both English and Arabic versions of the corpus of the Text Analysis Conference 2011 MultiLing Pilot by using ROUGE metrics. The evaluation results are promising in comparison to those of the participating systems. Indeed, our system achieved the best scores based on several ROUGE metrics.- Anthology ID:
- C18-1062
- Volume:
- Proceedings of the 27th International Conference on Computational Linguistics
- Month:
- August
- Year:
- 2018
- Address:
- Santa Fe, New Mexico, USA
- Editors:
- Emily M. Bender, Leon Derczynski, Pierre Isabelle
- Venue:
- COLING
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 734–744
- Language:
- URL:
- https://aclanthology.org/C18-1062
- DOI:
- Cite (ACL):
- Asma Al-Saleh and Mohamed El Bachir Menai. 2018. Ant Colony System for Multi-Document Summarization. In Proceedings of the 27th International Conference on Computational Linguistics, pages 734–744, Santa Fe, New Mexico, USA. Association for Computational Linguistics.
- Cite (Informal):
- Ant Colony System for Multi-Document Summarization (Al-Saleh & Menai, COLING 2018)
- PDF:
- https://preview.aclanthology.org/fix-dup-bibkey/C18-1062.pdf