An Intelligent Movies Recommendation System Based Facial Attributes Using Machine Learning
Küçük Resim Yok
Tarih
2023
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Movie theaters and platforms offer a wide selection of movies that require filtering to match the preferences of individual users. Recommender systems are an effective tool for this task. This study introduces a hybrid recommender system that combines collaborative filtering and content-based approaches to provide personalized movie recommendations. The proposed system considers age, gender, emotion, and genre attributes to ensure the suitability of the recommended movies. The proposed system targets the visitors of cinema theaters to try a new experience of choosing the next movie to watch by recognizing the visitor's face to determine his/her age, gender and emotion using camera. Therefore, our system is expected to achieve better results than traditional approaches. The system's performance is evaluated using standard metrics such as precision, recall, and F1-measure. The findings indicated that the proposed system outperforms the benchmark system in the most tested scenarios. However, the precision of the benchmark work is slightly higher in (8-14 and 15-24) age groups. © 2023 IEEE.
Açıklama
3rd International Conference on Emerging Smart Technologies and Applications, eSmarTA 2023 -- 10 October 2023 through 11 October 2023 -- Taiz -- 194050
Anahtar Kelimeler
face recognition, machine learning, movies recommendation, recommendation system
Kaynak
2023 3rd International Conference on Emerging Smart Technologies and Applications, eSmarTA 2023
WoS Q Değeri
Scopus Q Değeri
N/A
