A critical analysis of music recommendation systems and new perspectives

Perera, Dushani, Rajaratne, Maneesha, Arunathilake, Shiromi, Karunanayaka, Kasun and Liyanage, Buddy 2020. A critical analysis of music recommendation systems and new perspectives. Presented at: 2nd International Conference on Human Interaction and Emerging Technologies (IHIET-AI 2020), Lausanne, Switzerland, 23-25 April 2020. Published in: Ahram, Tareq, Taiar, Redha, Gremeaux-Bader, Vincent and Aminian, Kamiar eds. Human Interaction, Emerging Technologies and Future Applications II. Advances in Intelligent Systems and Computing. Human Interaction, Emerging Technologies and Future Applications II , vol.1152 International Conference on Human Interaction and Emerging Technologies: Springer Verlag, pp. 82-87. 10.1007/978-3-030-44267-5_12

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Abstract

Many businesses enhance on-line user experience using various recommender systems which have a growing innovation and research interest. Recommender systems in music streaming applications proactively suggest new selections to users by attempting to predict user preferences. While current music recommendation systems help users to efficiently discover fascinating music, challenges remain in this research area. This paper presents a critical analysis of current music recommender systems and proposes a new hybrid recommender system with efficient and enhanced prediction capabilities.

Item Type:	Conference or Workshop Item (Paper)
Date Type:	Published Online
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	Springer Verlag
ISBN:	9783030442675
ISSN:	2194-5357
Date of First Compliant Deposit:	8 December 2021
Last Modified:	17 May 2022 09:38
URI:	https://orca.cardiff.ac.uk/id/eprint/145695

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