In the last decade, recommender systems became an integral part of today's digital world. They help us to deal with today's information flood and to find information, services as well as products as books, movies or music we like. In particular, recommender systems are important for digital goods as the number of digital products increased dramatically in the last decade. This is, as those products have low production costs per unit accompanied by virtually no inventory- and transportation costs. Besides the challenge of finding items a user likes in this sheer number of available items, there is the challenge to consider the current context of the consumption or rather the user, i.e., the current time, the current activity or the current emotional state of a user. Today, the recommender systems and music information retrieval communities agree that context is inevitable to provide good personalized recommendations.
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