Content-based filtering algorithm for mobile recipe application

In general, people like to cook but they have no idea on what to cook and how to cook. Furthermore, they also wish to know certain recipes that suit to their preference. There are many cooking recipe websites but most of them do not provide suggestions for the user based on user´s food preferences. Current recipe suggestions developed by some researchers are mainly based on the collective interests, demographic information, and ingredients content. With respect to the problem mentioned previously, a content based mobile recipe application is proposed and tested in this paper. The main objective of this proposed application is to suggest a user preferred recipe using content-based filtering algorithm. Content-based filtering algorithm (CBFA) will be applied to identify the recipes that have high possibility for user to like. This algorithm will be able to recommend recipes based on user interaction. The algorithm will consider a few attributes to identify the similarity between the recipe pages viewed by the user. The reason to choose this algorithm is because it does not have the cold-start problem and it solely depends on the active user to identify their preferences. An Android based mobile recipe application is built to test this algorithm. The results from the experiment conducted show that the proposed algorithm is effective for recommending preferred recipes to user.