Learning to generate personalized product descriptions

Guy Elad, Ido Guy, Slava Novgorodov, Benny Kimelfeld, Kira Radinsky

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations


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, this is the first work 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.

Original languageEnglish
Title of host publicationCIKM 2019 - Proceedings of the 28th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Number of pages10
ISBN (Electronic)9781450369763
StatePublished - 3 Nov 2019
Externally publishedYes
Event28th ACM International Conference on Information and Knowledge Management, CIKM 2019 - Beijing, China
Duration: 3 Nov 20197 Nov 2019

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings


Conference28th ACM International Conference on Information and Knowledge Management, CIKM 2019

ASJC Scopus subject areas

  • Decision Sciences (all)
  • Business, Management and Accounting (all)


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