Guest Talk: "Context-Aware Music Recommender Systems" by Dr. Eva Zangerle (October 28th)
News from Oct 22, 2019
Eva Zangerle is a postdoctoral researcher at the University of Innsbruck at the research group for Databases and Information Systems (Department of Computer Science). She earned her PhD from the University of Innsbruck in the field of recommender systems for collaborative social media platforms. Her main research interests are within the fields of social media analysis, recommender systems and information retrieval.
In recent years, music aficionados have increasingly been consuming music via public music streaming platforms. Due to the size of the collections provided, music recommender systems have become a vital component for guiding the user through these collections. Particularly, music recommender systems aim to provide recommendations that match the user's current context as, throughout the day, users listen to music in numerous different contexts and situations. This not only requires capturing and modeling contextual information about the user but also incorporating such information into a music recommender system.
In this talk, I will present our work on (multi-) context-aware music recommender systems. Particularly, I will focus on context modeling approaches that allow to incorporate e.g., the musical and cultural background of users. Based on these user- and context-models, I will further elaborate on how we can build music recommenders tailored to user characteristics and contextual factors.
Date: October 28th, 2019
Location: Königin-Luise-Straße 24-26, 14195 Berlin, room 120