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https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

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When providing on-demand content on the internet, radio broadcasters risk losing the inherent flow of radio programs. Radio broadcasters have to understand how to automate editorial decisions and how to integrate them into personalized playouts. We conducted qualitative content analysis on radio content to identify sequences using pattern mining techniques. Based on the patterns of radio shows we identified, we propose an approach for automating editorial decisions to leverage the potential of value co-creation between broadcaster (in form of editorial value) and listener (in form of personalized content) in interactive internet radio.

Translating Editorial Work into Algorithms for Personalized Radio Streams