Leverage Social and Contextual Intelligence for Personalized Social Event Recommendation

Lien Fa Lin*, Yuan Ko Huang, Yung Ming Li

*Corresponding author for this work

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

Abstract

The O2O business model combines the efficiency of online retailing with the value created from physical customer experience. While many O2O apps and services have been proposed, accurately targeting customers and effectively advertising in a dynamic environment remain big challenges for O2O e-commerce. To address these challenges, we propose a novel social recommendation mechanism that incorporates social and contextual intelligence techniques. The proposed mechanism can identify the most suitable events for targeted users in a changing environment and significantly improve advertising effectiveness by considering the influence of friends.

Original languageEnglish
Title of host publicationProceedings - 2023 14th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages600-603
Number of pages4
ISBN (Electronic)9798350324228
DOIs
StatePublished - 2023
Event14th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2023 - Koriyama, Japan
Duration: 8 Jul 202313 Jul 2023

Publication series

NameProceedings - 2023 14th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2023

Conference

Conference14th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2023
Country/TerritoryJapan
CityKoriyama
Period8/07/2313/07/23

Keywords

  • Context-Awareness
  • Machine Learning
  • O2O
  • Social Computing

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