In order to maintain and improve health from the view point of eating, it is necessary to grasp the individual food preferences and to recommend appropriate meals. For that purpose, long-term food recordings is necessary. However, it is not easy to continuously record a meal. In my study, we predict individual food preferences by applying Matrix Factorization etc. to the FoodLog data. We show how much food preferences can be grasped using short-term food recordings.