Please use this identifier to cite or link to this item: https://rda.sliit.lk/handle/123456789/2019
Title: EEG Based Neuromarketing Recommender System for Video Commercials
Authors: Bandara, S. K
Wijesinghe, U. C
Jayalath, B. P
Bandara, S. K
Haddela, P. S
Wickramasinghe, L. M
Keywords: Video Commercials
EEG Based
Neuromarketing
Recommender System
Issue Date: 3-Jan-2022
Publisher: IEEE
Citation: S. K. Bandara, U. C. Wijesinghe, B. P. Jayalath, S. K. Bandara, P. S. Haddela and L. M. Wickramasinghe, "EEG Based Neuromarketing Recommender System for Video Commercials," 2021 IEEE 16th International Conference on Industrial and Information Systems (ICIIS), 2021, pp. 11-16, doi: 10.1109/ICIIS53135.2021.9660742.
Series/Report no.: 2021 IEEE 16th International Conference on Industrial and Information Systems (ICIIS);Pages 11-16
Abstract: Video commercials are well known and extremely popular because of the innovative progression in technology and competition in the business fields. Therefore, breaking down the effect of these video commercials are essential before the start of marketing and promotions. Mainly this study addresses a strategy that can assess the viability of movie commercials which are basically trailers, utilizing Electroencephalogram (EEG) signals caught from a Brain-Computer Interface (BCI). This helps the business to have a thought regarding the effect of the commercial and the value. The study consists of a recommend system which suggests movie advertisements based on the preferences of the users. The particular video will be evaluated from emotion, attention and enjoyment aspect of the user. Random Forest prediction algorithm with 91.97% accuracy was used for emotion analysis, c-Support Vector Classifier (c-svc) algorithm with 91.70% accuracy was used for attention analysis while using statistical approach Central Limit theorem and Empirical rule was used for enjoyment analysis to isolate particular emotion state. From the initial results received, confirms that the proposed framework is producing promising results. Although this research is currently focused on movie and entertainment industry, and also has the potential to be developed and applied in many other industries.
URI: http://rda.sliit.lk/handle/123456789/2019
ISSN: 2164-7011
Appears in Collections:Department of Information Technology-Scopes
Research Papers - IEEE
Research Papers - SLIIT Staff Publications
Research Publications -Dept of Information Technology

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