Abstract
The recommendation system collects and analyzes users’ preferences, and recommend information or commodities to users automatically. In this research, we developed an online book recommendation system based on users’ brainwave information. We collected users’ brainwave information by electroencephalography (EEG) device, and applied empirical mode decomposition (EMD) to decompose the brainwave signal into intrinsic mode functions (IMFs). A back-propagation neural networks (BPNN) model was developed to portrait the user’s brainwave-preference correlations based on IMFs of brainwave signals, and it was applied to design and develop the recommendation system. This research has highlighted a research direction about human computer interaction (HCI) design about recommendation system.
Recommended Citation
Chen, D N. and Jhang, Zhe-Lun, "A Personal Book Recommendation System Based on Brainwave Analysis" (2017). SIGHCI 2017 Proceedings. 8.
https://aisel.aisnet.org/sighci2017/8