Privacy-aware Social Music Playlist Generation

Listen to the music according to the taste of the people around you! We developed a system and implemented a mobile Android prototype and server system. We presented this work as a paper at the IEEE ICC 2016. You can find the full paper here (PDF).

Two of the most popular applications of smartphones are online social networking and playing back music. We present the design and implementation of a prototype that combines those usages by creating an architecture that allows the generation and playback of group music playlists that are based on the musical taste of individual guests attending a meeting. In our architecture, we utilize automatically collected data on smartphones for the automatized generation of group music playlists. We follow the idea of utilizing context data in a preprocessing step to generate a group music profile for the recommendation process that generates a group music playlist. For designing such an architecture, we consider current discussions on privacy, data ownership, and data control.

Screenshots of the app prototype we developed.
This shows the software architecture of our system.
This shows the process flow of a meeting.