New Profile Recommendation Approach Based on Multi-Criteria Algorithm

Actually, recommendation systems are widely used across the internet to assist users in finding products or services that fit their individual preferences. In this paper we present a new profile recommendation approach based on Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm. TOPSIS is a multi-criteria decision analysis algorithm. Our approach can be used in the context of flatsharing between persons. The goal is to suggest to a new user profile a set of room-mates profiles that are similar to his. Our approach is proposed to improve the relation between room-mates. In our context, we suppose that we have a set of room-mates profiles saved in a database. Each profile is defined according to its weight in a quantitative multi-criteria. The principle consist to recommend profiles saved in the database according to their similarity with the user profile. In our case, the similarity between profiles is defined as a minimization and/or maximization of distance between multi-criteria. The novelty of our approach is to recommend for each new user profile a set of similar profiles according to a good compromise between the multi-criteria distance. Experiments demonstrate the potential of our approach under different scenarios.