Online Recommender System for Radio Station Hosting

We describe a new recommender system for the Russian interactive radio network FMhost. The underlying model combines collaborative and user-based approaches. The system extracts information from tags of listened tracks for matching user and radio station profiles and follows an adaptive online learning strategy based on user history. We also provide some basic examples and describe the quality of service evaluation methodology.

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