4.7 Article

Food Recommendation: Framework, Existing Solutions, and Challenges

Journal

IEEE TRANSACTIONS ON MULTIMEDIA
Volume 22, Issue 10, Pages 2659-2671

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TMM.2019.2958761

Keywords

Artificial intelligence; knowledge based systems; image recognition; data mining; health information management

Funding

  1. National Natural Science Foundation of China [61532018, 61972378]
  2. Beijing Natural Science Foundation [L182054]
  3. National Program for Special Support of Eminent Professionals
  4. National Program for Support of Top-Notch Young Professionals
  5. StateKey Laboratory of Robotics

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A growing proportion of the global population is becoming overweight or obese, leading to various diseases (e.g., diabetes, ischemic heart disease and even cancer) due to unhealthy eating patterns, such as increased intake of food with high energy and high fat. Food recommendation is of paramount importance to alleviate this problem. Unfortunately, modern multimedia research has enhanced the performance and experience of multimedia recommendation in many fields such asmovies and POI, yet largely lags in the food domain. This article proposes a unified framework for food recommendation, and identifies main issues affecting food recommendation including incorporating various context and domain knowledge, building the personal model, and analyzing unique food characteristics. We then review existing solutions for these issues, and finally elaborate research challenges and future directions in this field. To our knowledge, this is the first survey that targets the study of food recommendation in the multimedia field and offers a collection of research studies and technologies to benefit researchers in this field.

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