Heterogeneous Information Network-based Music Recommendation System Using Deep Learning

Goonetilleka, Linuka

dc.contributor.author	Goonetilleka, Linuka
dc.date.accessioned	2024-03-13T07:37:56Z
dc.date.available	2024-03-13T07:37:56Z
dc.date.issued	2023
dc.identifier.citation	Goonetilleka, Linuka (2023) Heterogeneous Information Network-based Music Recommendation System Using Deep Learning. BSc. Dissertation, Informatics Institute of Technology	en_US
dc.identifier.issn	2019692
dc.identifier.uri	http://dlib.iit.ac.lk/xmlui/handle/123456789/1882
dc.description.abstract	The proposed system aims to enhance an existing music recommendation system using Heterogeneous Information Networks (HINs) and Graph Neural Networks (GNNs). It introduces a deep learning model to improve accuracy and performance. The framework captures diverse information, such as artist, song, genre details, user preferences, and listening history. The paper outlines a step-by-step methodology for incorporating HINs and GNNs in the recommendation process.	en_US
dc.language.iso	en	en_US
dc.publisher	IIT	en_US
dc.subject	Graph Neural Networks	en_US
dc.subject	Heterogenous Information Networks	en_US
dc.subject	Music	en_US
dc.title	Heterogeneous Information Network-based Music Recommendation System Using Deep Learning	en_US
dc.type	Thesis	en_US