Food Recommendation: Framework, Existing Solutions and Challenges
It provides a foundational survey for researchers in the multimedia field to tackle food recommendation, which is incremental as it synthesizes existing work.
This paper proposes a unified framework for food recommendation to address unhealthy eating patterns and related diseases, identifying key issues and reviewing existing solutions while highlighting research challenges and future directions.
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 as movies 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 building the personal model, analyzing unique food characteristics, incorporating various context and domain knowledge. 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.