Our food recommender system is to offer personalized and healthy recipe recommendations
By using Matrix Factorization algorithm to learn user’s preference, the system will provide recipe recommendations that suit user’s personal taste.
The recommended recipe not only takes user’s personal taste into account but also considers the user’s nutritional balance and personal health.
The system has integrated the wearable devices to track the user’s daily activities to generate real-time and calorie-balanced recommendation.
The system will help a group of users like a family to coordinate what to cook and deal with the tastes from different group members.
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Browse Our Recent Publication List
Mouzhi Ge, Francesco Ricci and David Massimo - ACM RecSys 2015
Mehdi Elahi, Mouzhi Ge, Francesco Ricci, Ignacio Fernández-Tobías, Shlomo Berkovsky, David Massimo - IntRS@ACM RecSys (2015)
Mouzhi Ge, Mehdi Elahi, Ignacio Fernández-Tobías, Francesco Ricci, David Massimo - ACM Digital Health 2015
Mouzhi Ge, Francesco Ricci, Floriano Zini - AIIA 2014
Mehdi Elahi, Mouzhi Ge, Francesco Ricci, David Massimo, Shlomo Berkovsky - ACM RecSys 2014
Take a closer look in more detail
Our team at the Free University of Bolzano, Italy
“Integrating Wearable Devices into Mobile Food Recommender System”
Mouzhi Ge, David Massimo, Francesco Ricci, and Floriano Zini - 7th International Conference on Mobile Computing, Applications and Services 2015