An Intelligent Movies Recommendation System Based Facial Attributes Using Machine Learning

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dc.contributor.authorBalfaqih, M.
dc.contributor.authorAltwaim, A.
dc.contributor.authorAlmohammedi, A.A.
dc.contributor.authorYusof, M.H.M.
dc.date.accessioned2024-09-29T16:20:57Z
dc.date.available2024-09-29T16:20:57Z
dc.date.issued2023
dc.departmentKarabük Üniversitesien_US
dc.description3rd International Conference on Emerging Smart Technologies and Applications, eSmarTA 2023 -- 10 October 2023 through 11 October 2023 -- Taiz -- 194050en_US
dc.description.abstractMovie 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.en_US
dc.description.sponsorshipUniversity of Jeddah, (UJ-21-DR-47)en_US
dc.identifier.doi10.1109/eSmarTA59349.2023.10293398
dc.identifier.isbn979-835030533-3
dc.identifier.scopus2-s2.0-85178114134en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/eSmarTA59349.2023.10293398
dc.identifier.urihttps://hdl.handle.net/20.500.14619/9450
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof2023 3rd International Conference on Emerging Smart Technologies and Applications, eSmarTA 2023en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectface recognitionen_US
dc.subjectmachine learningen_US
dc.subjectmovies recommendationen_US
dc.subjectrecommendation systemen_US
dc.titleAn Intelligent Movies Recommendation System Based Facial Attributes Using Machine Learningen_US
dc.typeConference Objecten_US

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