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Enhancing Content Recommendations in Podcast Platform
The chapter discusses the evolution of content recommendations in the ARD Audiothek platform, covering personalized rankings for podcasts based on user preferences, the usage of embeddings for personalization, and the challenges faced in adjusting the recommender system. It also explores collaborative learning techniques for personalized regulations, system improvements involving weighted matrix factorization, and the complexity of using various signals to predict user behavior in watching episodes.