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Application of Fuzzy Logic for Adaptive Food Recommendation

Author

Listed:
  • Tousif Osman

    (North South University, Dhaka, Bangladesh)

  • Maisha Mahjabeen

    (North South University, Dhaka, Bangladesh)

  • Shahreen Shahjahan Psyche

    (North South University, Dhaka, Bangladesh)

  • Afsana Imam Urmi

    (North South University, Dhaka, Bangladesh)

  • J.M. Shafi Ferdous

    (North South University, Dhaka, Bangladesh)

  • Rashedur M. Rahman

    (Department of Electrical Engineering and Computer Science, North South University, Dhaka, Bangladesh)

Abstract

The research introduces an adaptive food searching and recommending engine by taste and user preference using fuzzy logic. In contrast with existing system where food is searched by predefined keywords, this system searches food by its taste and users' preference which allows the system to provide better results. As food taste cannot be measured and user's preference is relative to each user, the authors have used concepts of artificial intelligence (AI) and fuzzy logic to better understand and deal the abstractness of these parameters. Along with food taste the authors have considered restaurant's environment, location, review and user's budget as searching parameters. The system includes a fuzzy database where food items of different restaurants with the specific parameters have been stored and gets updated by user feedback. System also maintains a user profile for individual user to adapt with individual user's choice of preference.

Suggested Citation

  • Tousif Osman & Maisha Mahjabeen & Shahreen Shahjahan Psyche & Afsana Imam Urmi & J.M. Shafi Ferdous & Rashedur M. Rahman, 2017. "Application of Fuzzy Logic for Adaptive Food Recommendation," International Journal of Fuzzy System Applications (IJFSA), IGI Global, vol. 6(2), pages 110-133, April.
    • Handle: RePEc:igg:jfsa00:v:6:y:2017:i:2:p:110-133
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