Addressing the Cold Start Problem in Recommender Systems
Iason Chaimalas worked with BBC to design a machine learning algorithm for Cold Start users that is both accurate and diverse. The method, called Bootstrapped Personalised Popularity (B2P), uses item metadata and popularity forecasting to increase accuracy and diversity, outperforming existing, highly performant models on severely cold datasets.
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