Development of Character Coordination System for Acquiring User Preference Rules

Abstract

In this study, we developed character coordination system using the Kansei retrieval agent model with fuzzy reasoning for acquisition user rules related to user preferences. The Kansei retrieval agent model imitates the sensitivity of each user. Previous research has demonstrated the effectiveness of the model in terms of presenting the user’s preferences by optimizing of fuzzy reasoning using numerical simulation and learning the user’s evaluation criteria. However, we have not verified the effectiveness for real users. Then, we developed a character coordination system using the model with fuzzy reasoning and extracted user’s preference rules. As a result, the developed system is effective in terms of acquiring preference rules that are the evaluation criteria of users.