Generating Summaries of Sets of Consumer Products: Learning from Experiments

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

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 language	English
Title of host publication	Proceedings of the 11th International Conference on Natural Language Generation
Publisher	ACL Anthology
Pages	403-407
Number of pages	5
ISBN (Print)	978-1-948087-86-5
Publication status	Published - Nov 2018
Event	11th International Conference on Natural Language Generation (INLG 2018) - Tilburg University, Tilburg, Netherlands Duration: 5 Nov 2018 → 8 Nov 2018

Conference

Conference	11th International Conference on Natural Language Generation (INLG 2018)
Country/Territory	Netherlands
City	Tilburg
Period	5/11/18 → 8/11/18

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Generating Summaries of Sets of Consumer Products
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Final published version, 1.64 MBLicence: CC BY

http://aclweb.org/anthology/W18-6548Licence: CC BY

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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 ., W18-6548 , ACL Anthology, pp. 403-407, 11th International Conference on Natural Language Generation (INLG 2018) , Tilburg, Netherlands, 5/11/18. <http://aclweb.org/anthology/W18-6548>

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title = "Generating Summaries of Sets of Consumer Products: Learning from Experiments",

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{\textquoteright} understanding of the domain.",

author = "Kittipitch Kuptavanich and Ehud Reiter and {Van Deemter}, Kees and Advaith Siddharthan",

year = "2018",

month = nov,

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AU - Siddharthan, Advaith

PY - 2018/11

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N2 - 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.

AB - 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.

M3 - Published conference contribution

SN - 978-1-948087-86-5

SP - 403

EP - 407

BT - Proceedings of the 11th International Conference on Natural Language Generation

PB - ACL Anthology

Y2 - 5 November 2018 through 8 November 2018

ER -

Generating Summaries of Sets of Consumer Products: Learning from Experiments

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