  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.
