#27: Recommender Systems at the BBC with Alessandro Piscopo and Duncan Walker

In episode 27 of Recsperts, we meet Alessandro Piscopo, Lead Data Scientist in Personalization and Search, and Duncan Walker, Principal Data Scientist in the iPlayer Recommendations Team, both from the BBC. We discuss how the BBC personalizes recommendations across different offerings like news or video and audio content recommendations. We learn about the core values for the oldest public service media organization and the collaboration with editors in that process.The BBC once started with short video recommendations for BBC+ and nowadays has to consider recommendations across multiple domains: news, the iPlayer, BBC Sounds, BBC Bytesize, and more. With a reach of about 500M+ users who access services every week there is a huge potential. My guests discuss the challenges of aligning recommendations with public service values and the role of editors and constant exchange, alignment, and learning between the algorithmic and editorial lines of recommender systems.We also discuss the potential of cross-domain recommendations to leverage the content across different products as well as the organizational setup of teams working on recommender systems at the BBC. We learn about skews in the data due to the nature of an online service that also has a linear offering with TV and radio services.Towards the end, we also touch a bit on QUARE @ RecSys, which is the Workshop on Measuring the Quality of Explanations in Recommender Systems.Enjoy this enriching episode of RECSPERTS - Recommender Systems Experts.Don't forget to follow the podcast and please leave a review(00:00) - Introduction (03:10) - About Alessandro Piscopo and Duncan Walker (14:53) - RecSys Applications at the BBC (20:22) - Journey of Building Public Service Recommendations (28:02) - Role and Implementation of Public Service Values (36:52) - Algorithmic and Editorial Recommendation (01:01:54) - Further RecSys Challenges at the BBC (01:15:53) - Quare Workshop (01:23:27) - Closing Remarks Links from the Episode:Alessandro Piscopo on LinkedInDuncan Walker on LinkedInBBCQUARE @ RecSys 2023 (2nd Workshop on Measuring the Quality of Explanations in Recommender Systems)Papers:Clarke et al. (2023): Personalised Recommendations for the BBC iPlayer: Initial approach and current challengesBoididou et al. (2021): Building Public Service Recommenders: Logbook of a JourneyPiscopo et al. (2019): Data-Driven Recommendations in a Public Service OrganisationGeneral Links:Follow me on LinkedInFollow me on XSend me your comments, questions and suggestions to marcel.kurovski@gmail.comRecsperts Website

Om Podcasten

Recommender Systems are the most challenging, powerful and ubiquitous area of machine learning and artificial intelligence. This podcast hosts the experts in recommender systems research and application. From understanding what users really want to driving large-scale content discovery - from delivering personalized online experiences to catering to multi-stakeholder goals. Guests from industry and academia share how they tackle these and many more challenges. With Recsperts coming from universities all around the globe or from various industries like streaming, ecommerce, news, or social media, this podcast provides depth and insights. We go far beyond your 101 on RecSys and the shallowness of another matrix factorization based rating prediction blogpost! The motto is: be relevant or become irrelevant! Expect a brand-new interview each month and follow Recsperts on your favorite podcast player.