An attempt of development of a recommender system for user group using rough sets

Abstract

In this paper, we propose a recommender system for user group using rough sets. In recent years, with the advancement of information technology, recommender systems have been used in various services. On the other hand, recommender systems for multiple people are not as mainstream as those for a single person. The proposed method aims at providing recommendations that evenly reflects the opinions of multiple people in the user grope. In experiments, we used Rakuten Recipe data. As a result, the result of the questionnaire administered to the subjects showed that the average satisfaction level was higher than that of content-based filtering. In addition, we found that the recipes recommended by the recommendation method tended to have a large number of tags. analysis of rankings using decision rules.