Generating Summaries of Sets of Consumer Products: Learning from Experiments

Kittipitch Kuptavanich, Ehud Reiter, Kees Van Deemter, Advaith Siddharthan

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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.
Original languageEnglish
Title of host publicationProceedings of the 11th International Conference on Natural Language Generation
PublisherACL Anthology
Pages403-407
Number of pages5
ISBN (Print)978-1-948087-86-5
Publication statusPublished - Nov 2018
Event11th International Conference on Natural Language Generation (INLG 2018) - Tilburg University, Tilburg, Netherlands
Duration: 5 Nov 20188 Nov 2018

Conference

Conference11th International Conference on Natural Language Generation (INLG 2018)
CountryNetherlands
CityTilburg
Period5/11/188/11/18

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Kuptavanich, K., Reiter, E., Van Deemter, K., & Siddharthan, A. (2018). Generating Summaries of Sets of Consumer Products: Learning from Experiments. In Proceedings of the 11th International Conference on Natural Language Generation (pp. 403-407). [W18-6548 ] ACL Anthology. http://aclweb.org/anthology/W18-6548