Overview of Approaches and Future Challenges for Development of Music Recommendation Socio-Technical Systems

Abstract

This paper analyses the position of music recommendations in the wider context of music information behavior research and proposes five music information behavior dimensions: socio-cognitive information experience, information seeking, information retrieval, recommendations, and content consumption and analysis. It examines different approaches in the development of music recommendation systems (RS) which are applicable to all types of web information resources. These approaches are classified as content-based, collaborative, demographic, knowledge-based, meta-data-based, emotion-based and context-based, while the hybrid approach to RS development combines two or more approaches into one. Also, recent developments in the domain of music recommendations are discussed in detail. Finally, challenges and opportunities for collaboration between the scientific and the commercial communities on the development of new RS models are being explored.