Mining KANSEI fuzzy rules from photos on the internet
Hajime Hotta, Ayumi Takano, Masafumi Hagiwara · 2008
In this paper, we propose a method of mining KANSEI fuzzy rules from photos on the Internet. KANSEI is a Japanese word which means human impressions and KANSEI engineering is a method for translating KANSEI into product parameters through the analysis of data. In KANSEI engineering, some quantitative data are required for analyzing KANSEI and conventional approach uses questionnaire to collect quantitative data. However, questionnaire tends to become strained for subjects in order to collect enough data. The proposed method is an improved version of the method which authors have proposed. With the conventional system, fuzzy rules of KANSEI can be extracted from some questionnaire data and the system also requires heavy questionnaire surveys. The main purpose of the proposed method is to enable the method to work without questionnaire data by using photo data and tags on the Internet. By preparing learning data from the Internet and improving algorithms, the proposed method can extract fuzzy rules of correspondence of colors to impressions. The experimental results show that the proposed method worked efficiently.