Generating Summaries of Sets of Consumer Products: Learning from Experiments
Kittipitch Kuptavanich, Ehud Reiter, Kees Van Deemter, Advaith Siddharthan
Abstract
We explored the task of creating a textual summary describing a large set of objects characterised by a small number of features using an e-commerce dataset. When a set of consumer products is large and varied, it can be difficult for a consumer to understand how the products in the set differ; consequently, it can be challenging to choose the most suitable product from the set. To assist consumers, we generated high-level summaries of product sets. Two generation algorithms are presented, discussed, and evaluated with human users. Our evaluation results suggest a positive contribution to consumers’ understanding of the domain.- Anthology ID:
- W18-6548
- Volume:
- Proceedings of the 11th International Conference on Natural Language Generation
- Month:
- November
- Year:
- 2018
- Address:
- Tilburg University, The Netherlands
- Editors:
- Emiel Krahmer, Albert Gatt, Martijn Goudbeek
- Venue:
- INLG
- SIG:
- SIGGEN
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 403–407
- Language:
- URL:
- https://aclanthology.org/W18-6548
- DOI:
- 10.18653/v1/W18-6548
- Cite (ACL):
- Kittipitch Kuptavanich, Ehud Reiter, Kees Van Deemter, and Advaith Siddharthan. 2018. Generating Summaries of Sets of Consumer Products: Learning from Experiments. In Proceedings of the 11th International Conference on Natural Language Generation, pages 403–407, Tilburg University, The Netherlands. Association for Computational Linguistics.
- Cite (Informal):
- Generating Summaries of Sets of Consumer Products: Learning from Experiments (Kuptavanich et al., INLG 2018)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/W18-6548.pdf