Implicit Feedback-based Group Recommender System for Internet of Things Applications

Zhiwei Guo, Keping Yu, Tan Guo, Ali Kashif Bashir, Muhammad Imran, Mohsen Guizani

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

With the prevalence of Internet of Things (IoT)-based social media applications, the distance among people has been greatly shortened. As a result, recommender systems in IoT-based social media need to be developed oriented to groups of users rather than individual users. However, existing methods were highly dependent on explicit preference feedbacks, ignoring scenarios of implicit feedbacks. To remedy such gap, this paper proposes an implicit feedback-based group recommender system using probabilistic inference and non-cooperative game (GREPING) for IoT-based social media. Particularly, unknown process variables can be estimated from observable implicit feedbacks via Bayesian posterior probability inference. In addition, the globally optimal recommendation results can be calculated with the aid of non-cooperative game. Two groups of experiments are conducted to assess the GREPING from two aspects: efficiency and robustness. Experimental results show obvious promotion and considerable stability of the GREPING compared to baseline methods.

Original languageEnglish
Title of host publication2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728182988
DOIs
Publication statusPublished - 2020 Dec
Event2020 IEEE Global Communications Conference, GLOBECOM 2020 - Virtual, Taipei, Taiwan, Province of China
Duration: 2020 Dec 72020 Dec 11

Publication series

Name2020 IEEE Global Communications Conference, GLOBECOM 2020 - Proceedings
Volume2020-January

Conference

Conference2020 IEEE Global Communications Conference, GLOBECOM 2020
CountryTaiwan, Province of China
CityVirtual, Taipei
Period20/12/720/12/11

Keywords

  • group recommender systems
  • implicit feedback
  • Internet of Things
  • probabilistic inference

ASJC Scopus subject areas

  • Media Technology
  • Modelling and Simulation
  • Instrumentation
  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Software
  • Safety, Risk, Reliability and Quality

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