research-article

Learning to Generate Personalized Product Descriptions

Authors:

Slava Novgorodov,

Benny Kimelfeld,

Kira RadinskyAuthors Info & Claims

CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge Management

Pages 389 - 398

https://doi.org/10.1145/3357384.3357984

Published: 03 November 2019 Publication History

Abstract

Personalization plays a key role in electronic commerce, adjusting the products presented to users through search and recommendations according to their personality and tastes. Current personalization efforts focus on the adaptation of product selections, while the description of a given product remains the same regardless of the user who views it. In this work, we propose an approach to personalize product descriptions according to the personality of an individual user. To the best of our knowledge, we are the first to address the problem of generating personalized product descriptions. We first learn to predict a user's personality based on past activity on an e-commerce website. Then, given a user personality, we propose an extractive summarization-based algorithm that selects the sentences to be used as part of a product description in accordance with the given personality. Our evaluation shows that user personality can be effectively learned from past e-commerce activity, while personalized descriptions can lead to a higher interest in the product and increased purchase likelihood.

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Rodriguez-Diaz CJimenez SBejarano DBernal-Chávez JGelbukh A(2023)Measuring Semantic Gap between user-generated content and product descriptions through compression comparison in e-commerceInformation Sciences10.1016/j.ins.2023.118953(118953)Online publication date: Apr-2023
https://doi.org/10.1016/j.ins.2023.118953
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Index Terms

Learning to Generate Personalized Product Descriptions

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cover image ACM Conferences

CIKM '19: Proceedings of the 28th ACM International Conference on Information and Knowledge Management

November 2019

3373 pages

ISBN:9781450369763

DOI:10.1145/3357384

General Chairs:
Wenwu Zhu
Tsinghua University, China
,
Dacheng Tao
University of Massachusetts, USA
,
Xueqi Cheng
Institute of Computing Technology, CAS, China
,
Program Chairs:
Peng Cui
Tsinghua University, China
,
Elke Rundensteiner
Worcester Polytechnic Institute, USA
,
David Carmel
Amazon Research, USA
,
Qi He
LinkedIn, USA
,
Jeffrey Xu Yu
Chinese University of Hong Kong, China

Copyright © 2019 ACM.

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Published: 03 November 2019

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November 3 - 7, 2019

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CIKM '19 Paper Acceptance Rate 202 of 1,031 submissions, 20%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Cited By

Fong BSee JJin CHe LSong MWang R(2024)BrandDiffusion: Multimodal Personalized Marketing Visual Content GenerationProceedings of the 2nd International Workshop on Multimedia Content Generation and Evaluation: New Methods and Practice10.1145/3688867.3690175(72-77)Online publication date: 28-Oct-2024
https://dl.acm.org/doi/10.1145/3688867.3690175
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
Rodriguez-Diaz CJimenez SBejarano DBernal-Chávez JGelbukh A(2023)Measuring Semantic Gap between user-generated content and product descriptions through compression comparison in e-commerceInformation Sciences10.1016/j.ins.2023.118953(118953)Online publication date: Apr-2023
https://doi.org/10.1016/j.ins.2023.118953
Deng YLi YZhang WDing BLam W(2022)Toward Personalized Answer Generation in E-Commerce via Multi-perspective Preference ModelingACM Transactions on Information Systems10.1145/350778240:4(1-28)Online publication date: 9-Mar-2022
https://dl.acm.org/doi/10.1145/3507782
Wang RChen ZZhang MLi ZLiu ZDang ZYu CChen XKitamura YQuigley AIsbister KIgarashi TBjørn PDrucker S(2021)Revamp: Enhancing Accessible Information Seeking Experience of Online Shopping for Blind or Low Vision UsersProceedings of the 2021 CHI Conference on Human Factors in Computing Systems10.1145/3411764.3445547(1-14)Online publication date: 6-May-2021
https://dl.acm.org/doi/10.1145/3411764.3445547
Novgorodov SGuy IElad GRadinsky K(2020)Descriptions from the CustomersACM Transactions on Internet Technology10.1145/341820220:4(1-31)Online publication date: 6-Oct-2020
https://dl.acm.org/doi/10.1145/3418202
Tzaban HGuy IGreenstein-Messica ADagan ARokach LShapira BHuang JChang YCheng XKamps JMurdock VWen JLiu Y(2020)Product Bundle Identification using Semi-Supervised LearningProceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3397271.3401128(791-800)Online publication date: 25-Jul-2020
https://dl.acm.org/doi/10.1145/3397271.3401128

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