Web-Based Intelligent Book Recommendation System Under Smart Campus Applications
Küçük Resim Yok
Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Science and Business Media Deutschland GmbH
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Recommendation systems are essential as they help users to discover new books and resources and increase their engagement and satisfaction, thus improving the overall learning experience. This paper presents a web-based intelligent book recommendation system for smart campus applications at Izmir Bakircay University. The system is designed as an intelligent hybrid tool that combines collaborative and content-based filtering techniques to recommend books to users with methodological differences. It considers the user’s reading history and preferences and integrates with other smart campus applications to provide personalized recommendations. The system is important for the digital transformation of smart campuses as it helps to make education more personalized, efficient, and data-driven. Also, it allows for the effective use of public resources. The effectiveness of the system was evaluated through user feedbacks, 22 users evaluated 148 books and the results showed that users responded positively to about 70% of the recommended books thus, it provided accurate and personalized recommendations. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
Açıklama
12th International Symposium on Intelligent Manufacturing and Service Systems, IMSS 2023 -- 26 May 2023 through 28 May 2023 -- -- 302369
Anahtar Kelimeler
book recommendation; intelligent system; smart campus; web application, Collaborative filtering; Intelligent systems; Metadata; Websites; Book recommendation; Collaborative-based filtering; Content based filtering; Filtering technique; Learning experiences; Personalized recommendation; Smart campus; WEB application; Web applications; Web based; Recommender systems
