Estudio y análisis de técnicas de consenso para recomendadores grupales

Abstract

Every day a lot of people search on internet reviews of others about a product before they buy it. This is due to the fact that the recommender system was created. A recommender system displays a list of products according to the user preferences. There are many types of recommenders: content based, collaborative filtering... Most of them focus on making recommendations to a single user. In this degree final project, we focus to study group recommenders and consensus strategies. This porject employs three types of strategies to achieve users consensus. We’re going to apply these strategies to groups of different sizes and similarities. Finally, we’ll analyze users satisfactions with different strategies in each of these groups to conclude what methods are better.