Personality based recipe recommendation using recipe network graphs

Abstract

There is usually a vast amount of information that people have to sift through when searching for recipes online. In addition to looking at the ingredient list, people tend to read the reviews of recipes to decide if it is appealing to them based on the feedback of others who have prepared the recipe, with some recipes having hundreds of reviews. Several researchers have proposed recipe-based recommendation systems using details such as the nutritional information of the recipe, however, such recommendations are not personalized to the characteristics of the user. To contribute to research in this area, we propose a personalized recommendation system that makes suggestions to users based on their personality. People of the same personality tend to have many similarities, and personality is a predictor of behavior, we thus propose that the use of personality types could make recommendations more personalized. In this paper, we present the result of a preliminary investigation into the use of the personality of reviewers of recipes and a recipe-based network graph in recommending recipes to users.