Situation-based food recommendation for yielding good results

We propose a method for finding such foods that yield good results to a user based on the user´s situation and showing the recommending foods with the evidence of the foods yielding good results so that the user is convinced to choose the food. We focus on the following problems: (1) existing recommendation systems only focus on “who chooses what” but people is not always able to select the best one which yields good result; (2) even though the proposed method finds the suitable foods, it is not sufficient to simply recommend them because users cannot understand why the foods are good. To address these problems, we construct a model by analyzing food related tweets on the Twitter. In our experiments, we demonstrate that the proposed method successfully avoided recommending a food which yields a bad result and providing evidence in addition to the recommendation foods is beneficial for decision making of food.