Social Media Mining for Multimodal Music Retrieval

Online social media has been seeing an incredible boom during the last couple of years. Even though they are researched heavily by the Data Mining and Information Retrieval communities, mining, analyzing, and exploiting the user-generated data offered on various platforms such as Twitter, Facebook, or Youtube, is still underrepresented in the context of Music Information Retrieval (MIR). Hence, in this project we propose to comprehensively research the use of a large number of different user-generated data sources for several innovative tasks in MIR research. To this end, we identified three goals that will be thoroughly addressed: 1. Inferring Geospatial Listening Patterns from User-generated Data 2. Multimodal Modeling for Serendipitous Music Access 3. Building Intelligent, Adaptive User Interfaces to Music Collections