CCS CONCEPTS
The problem of recommending food to people has recently become an active field of research. While there is growing body of work investigating how online food recommender systems could potentially be designed to better meet the users’ preferences, to date less research has tried to understand the nature of online food choices and their complexity. How do people make their food choices online? To what extent can we model and predict this behavior, and can we actually change it through recommender technology?
Why might we want to change behavior? According to the World Health Organization around 80% of cases of heart disease, strokes and type 2 diabetes could be avoided if people would implement a healthier diet. Health-aware food recommender technologies have been touted as a valuable asset in achieving the ambitious goal of developing systems, which positively impact on the food choices people make. For example, they may help people to implement a healthier diet by suggesting healthier versions of a similar meal they typically like.
In this talk, I will present our latest research on the online food recommender problem. I will reveal the complex nature of online food choices and how this knowledge can be used to build novel food recommender systems. To conclude, I will present some preliminary work aiming to nudge people towards healthier food choices. • Information systems → Recommender systems. Food recommendation, Health recommender systems