Recommendations are crucial for the success of large websites. While there are many ways to determine recommendations, the relative quality of these recommenders depends on many f...
Current conversational recommender systems are unable to offer guarantees on the quality of their recommendations due to a lack of principled user utility models. We develop an ap...
Abstract. This paper introduces a framework based on multi-agent system for solving problems of combinatorial optimization. The framework allows running various metaheuristic algor...
Abstract Previously, we have proposed two recommendation systems, the Context-aware Information Filtering (C-IF) and Context-aware Collaborative Filtering (C-CF), both of which ar...
Kenta Oku, Shinsuke Nakajima, Jun Miyazaki, Shunsu...