research-article

Descriptions from the Customers: Comparative Analysis of Review-based Product Description Generation Methods

Authors:

Slava Novgorodov,

Kira RadinskyAuthors Info & Claims

ACM Transactions on Internet Technology (TOIT), Volume 20, Issue 4

Article No.: 44, Pages 1 - 31

https://doi.org/10.1145/3418202

Published: 06 October 2020 Publication History

Abstract

Product descriptions play an important role in the e-commerce ecosystem. Yet, on leading e-commerce websites product descriptions are often lacking or missing. In this work, we suggest to overcome these issues by generating product descriptions from user reviews. We identify the set of candidates using a supervised approach that extracts review sentences in their original form, diversifies them, and selects the top candidates. We present extensive analyses of the generated descriptions, including a comparison to the original descriptions and examination of review coverage. We also perform an A/B test that demonstrates the impact of presenting our descriptions on user traffic.

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Descriptions from the Customers: Comparative Analysis of Review-based Product Description Generation Methods

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cover image ACM Transactions on Internet Technology

ACM Transactions on Internet Technology Volume 20, Issue 4

November 2020

391 pages

ISSN:1533-5399

EISSN:1557-6051

DOI:10.1145/3427795

Editor:
Ling Liu
Georgia Institute of Technology, USA

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Publication History

Published: 06 October 2020

Accepted: 01 July 2020

Revised: 01 June 2020

Received: 01 December 2019

Published in TOIT Volume 20, Issue 4

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Zhao ZZhang LLian XGao XLv HShi L(2023)ReqGen: Keywords-Driven Software Requirements GenerationMathematics10.3390/math1102033211:2(332)Online publication date: 9-Jan-2023
https://doi.org/10.3390/math11020332
Verma JBhargav SBhavsar MBhattacharya PBostani AChowdhury SWebber JMehbodniya A(2023)Graph-Based Extractive Text Summarization Sentence Scoring Scheme for Big Data ApplicationsInformation10.3390/info1409047214:9(472)Online publication date: 22-Aug-2023
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Guo XWang SZhao HDiao SChen JDing ZHe ZLu JXiao YLong BYu HWu L(2023)Intelligent online selling point extraction and generation for e‐commerce recommendationAI Magazine10.1002/aaai.1208344:1(16-29)Online publication date: 5-Apr-2023
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Fukumoto KSuzuki RTerada HBato MNadamoto A(2021)Comparison of Deep Learning Models for Automatic Generation of Product Description on E-commerce siteThe 23rd International Conference on Information Integration and Web Intelligence10.1145/3487664.3487696(223-231)Online publication date: 29-Nov-2021
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