USING RECOGNIZED EMOTION AS IMPLICIT FEEDBACK FOR A RECOMMENDER SYSTEM
DOI:
https://doi.org/10.26906/SUNZ.2023.3.115Keywords:
deep neural network with immersion layers, extended reality, immersiveness, 3D convolutional neural networkAbstract
Topicality. Due to the growing of digitalization of art, the tasks of improving immersiveness during user interaction with extended reality art systems arise. Research methods. Deep Neural Network with Immersion Layers, 3D Convolutional Neural Network. The purpose of the article: Improving the selection of the most relevant videos by using recognized user emotions as implicit feedback in the recommender system of virtual art compositions. The results obtained. A system was developed for classifying the user's emotions in the video, further calculating the emotional scoring and using the obtained value as implicit feedback for the recommender system for selecting the most relevant videos for creating virtual art compositions. The combination of the presented methods will allow to improve the personalization of recommendations and increase its immersiveness during user interaction with virtual art compositions. Conclusion. The approach developed in the work can be used to improve the immersiveness and personalization of recommendations during user interaction with extended reality art systems.Downloads
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