Tagged with: Personalisation, Recommendations and Content Discovery
Posts (20)
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Introducing machine-based video recommendations in Ö÷²¥´óÐã Sport
Robert Heap
Executive Product Manager, Ö÷²¥´óÐã Sport
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Philip 21 - an interactive story exploring race, love and modern Britain
Joey Amoah
Development Producer
An object-based media experience - a story of a date with a young black man, turned into an introspective examination of race, love and modern Britain. Here are the techniques and mechanics underpinning this and other branching narrative experiences, examining how they keep audiences engaged.
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Building a WebAssembly Runtime for Ö÷²¥´óÐã iPlayer and enhanced audience experiences
Juliette Carter
Research Engineer, Ö÷²¥´óÐã R&D
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The complexities of creating a new 'follow topic' capability
Dave Lee
Senior Architect, Ö÷²¥´óÐã Ö÷²¥´óÐã
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Me, you and the machine
Matthew Postgate
Chief Technology and Product Officer, Ö÷²¥´óÐã D&E
The Ö÷²¥´óÐã's Chief Technology and Product Officer explains how the corporation can benefit from Machine Learning.
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How metadata will drive content discovery for the Ö÷²¥´óÐã online
Jonathan Murphy and Jeremy Tarling
Digital Publishing, Design & Engineering
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Understanding public service curation: What do ‘good’ recommendations look like?
Anna McGovern
Executive Producer, Recommendations
Examining the qualities required to create good recommendations for the Ö÷²¥´óÐã's digital content.
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Scaling responsible machine learning at the Ö÷²¥´óÐã
Gabriel Straub
Head of Data Science and Architecture, Ö÷²¥´óÐã D&E
How the Ö÷²¥´óÐã's public service principles are being applied to machine learning.
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Navigating the data ecosystem technology landscape
Hannes Ricklefs, Max Leonard
Ö÷²¥´óÐã Design and Engineering
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Machine learning and editorial collaboration within the Ö÷²¥´óÐã
Anna McGovern, Ewan Nicolson, Svetlana Videnova
Datalab team