BROWSE
Detail
Conference Paper
Measuring User Preferences Using EEG-based User Responses
Cited - time in 
Share 
Share
- Authors
- Jinyoung Moon, Youngrae Kim, Hyungjik Lee, Changseok Bae, Wan C. Yoon
- Issue Date
- 2013-07
- Citation
- International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) 2013, pp.1-3
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- Measuring user preferences while a user views a video is essential for predicting success of video contents, such as films, music videos, and television commercials before their releases. Because the EEGbased studies on preference are in their early age, their methods are inadequate for measuring user preference accurately. For this, we proposed a classification model for four categorized preference classes and a prediction model for real-valued preference levels by using EEG-based user responses. The average classification accuracy of models using band power was 97.38%. In addition, the proposed preference level of real-values reflected long-term trends of preference as well as short-term fluctuations of preference.
- KSP Keywords
- Band Power, Classification models, Long-term trends, Predicting success, Preference level, Real-valued, Short-term fluctuations, User preference, User views, Video content, classification accuracy