This paper presents preference measurement of user using user response electroencephalogram (EEG). Today users are faced with overflowing image data and images are sorted with time, location, and event. In this paper we introduce a noble way to pick out the preferred image using user response EEG wave. The EEG wave data are gathered through experiment using consumer grade EEG device sensors. Images were classified into preferred image and unnoticed images. The accuracy of image classification using gathered EEG wave was 88.54%. Also we found significant difference of alpha waves on position F8 and T8 between EEG wave recorded during preferred images and not preferred images. Using this analysis, we are able to service preference based personalized service.
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