Trends and Challenges in Developing Context-Aware Music Recommendation Systems

The development of computer technology and the Internet influence how people buy, save, and listen to music. Today, there are millions of songs that everyone can choose to listen anytime and anywhere. One of many problems arise is, the music listeners are often spending too much time and giving much effort in choosing music to be listened, thus a music recommendation system is needed. Context are important in music recommendation system, people prefer different music for certain activities, or in other words, people would have a different music selection for a certain context. For example, a user who is exercising will prefer a loud and energizing music, a user who is relaxing will prefer a soft and soothing music. This review is focused on trends and challenges in developing context-aware music recommendation system, which uses context as primary features or data to recommend music. Developing context-aware music recommendation system is challenging, it is complicated to meet the users needs and requirements. The challenges are come from the great amount of data needed, how to choose context used in the research, cold start, and generating a dynamic playlist.