Abstract
It has been known to be difficult to generate adequate sports updates from a sequence of vast amounts of diverse live tweets, although the live sports viewing experience with tweets is gaining the popularity. In this paper, we focus on soccer matches and work on building a system to generate live updates for soccer matches from tweets so that users can instantly grasp a match’s progress and enjoy the excitement of the match from raw tweets. Our proposed system is based on a large pre-trained language model and incorporates a mechanism to control the number of updates and a mechanism to reduce the redundancy of duplicate and similar updates.- Anthology ID:
- 2023.emnlp-main.624
- Volume:
- Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
- Month:
- December
- Year:
- 2023
- Address:
- Singapore
- Editors:
- Houda Bouamor, Juan Pino, Kalika Bali
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 10100–10106
- Language:
- URL:
- https://aclanthology.org/2023.emnlp-main.624
- DOI:
- 10.18653/v1/2023.emnlp-main.624
- Cite (ACL):
- Masashi Oshika, Kosuke Yamada, Ryohei Sasano, and Koichi Takeda. 2023. Transformer-based Live Update Generation for Soccer Matches from Microblog Posts. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, pages 10100–10106, Singapore. Association for Computational Linguistics.
- Cite (Informal):
- Transformer-based Live Update Generation for Soccer Matches from Microblog Posts (Oshika et al., EMNLP 2023)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2023.emnlp-main.624.pdf