Online book recommendation system

dc.contributor.authorJayathilake, N
dc.contributor.authorKahapola, K
dc.contributor.authorKariyawasam, L
dc.contributor.editorGunawardena, S
dc.date.accessioned2025-11-20T06:38:05Z
dc.date.issued2025
dc.description.abstractWith the growing number of books, finding relevant content is challenging. We developed an Online Book Recommendation System using a hybrid approach combining contentbased and collaborative filtering, ensuring personalized and diverse recommendations.
dc.identifier.conferenceApplied Data Science & Artificial Intelligence (ADScAI) Symposium 2025
dc.identifier.departmentDepartment of Computer Science & Engineering
dc.identifier.doihttps://doi.org/10.31705/ADScAI.2025.46
dc.identifier.emailnipuni.21@cse.mrt.ac.lk
dc.identifier.emailkaushal.21@cse.mrt.ac.lk
dc.identifier.emaillakindu.21@cse.mrt.ac.lk
dc.identifier.facultyEngineering
dc.identifier.placeMoratuwa, Sri Lanka
dc.identifier.proceedingroceedings of Applied Data Science & Artificial Intelligence Symposium 2025
dc.identifier.urihttps://dl.lib.uom.lk/handle/123/24407
dc.language.isoen
dc.publisherDepartment of Computer Science and Engineering
dc.subjectbook recommendation
dc.subjectcollaborative filtering
dc.subjectLightgcn
dc.titleOnline book recommendation system
dc.typeConference-Extended-Abstract

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