Abstract
In searching picture images, music, perfumes and apparels, etc., it is difficult to find the object that users want through conventional keyword search methods. To cope with this problem, the searches by kansei-words and by kansei-vectors are proposed. The kansei-vector is an array of the value that indicates a degree of each kansei-word. However, due to the gap between user's subjective kansei image value and the corresponding kansei image value stored in the database, a problem occurs that the search result is different from what users want. This paper proposes the search method to resolve such a subjective criteria gap. This method automatically decreases such gaps using the user's searching history and Fuzzy modeling. This method can avoid users' burden unlike conventional methods such as ones using questionnaires. Small size experimental results showed users can do satisfactory search based on their subject image learned quickly by the proposed method.
