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Using Food Recommender Systems to Promote Healthy Choices

Online grocery shopping has many opportunities for algorithmic and interface personalization. Whereas ‘offline’ supermarkets can only offer their products in one format for everyone, online shops have the possibility to provide real-time personalized advice to support healthier food choices. While it may be tempting to employ personalization approaches from other domains (e.g., movie recommendation in Netflix, music recommendation on Spotify), the challenges in the domain of food recommendation are distinct, for it also involves behavioural change. Hence, recommenders should not only optimize short-term engagement, but also consider long-term factors, such as habit formation and acquired taste.

In this project, the main goal is prepare a larger grant application. We seek to combine knowledge on recommender algorithms, digital food marketing and nutrition in a project on human-computer interaction. The end goal is to develop novel algorithms that are sensitive to changes in user preferences and evaluate to what extent they can support users’ healthy eating goals in an online supermarket.