Hybrid recommendation based on implicative rating measures

Abstract

This paper proposes the implicative rating measures and the hybrid recommendation model based on those measures to suggest a list of top N items to an active user. The proposed recommendation model is the combination of the user-based collaborative filtering approach and the association rule based approach. This hybrid model are compared to some existing models such as the popular model, the item based collaborative filtering using the Jaccard measure, the user based collaborative filtering using the Jaccard measure, the latent factor model, and the association rule based model using the Confidence measure on two datasets CourseRegistration and MSWeb. The experimental results show that the performance of the proposed model is better than that of the compared models.