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Tagged with: Personalisation, Recommendations and Content Discovery

Posts (20)

  1. Introducing machine-based video recommendations in BBC Sport

    Robert Heap

    Executive Product Manager, BBC Sport

    Introducing machine-based video recommendations in BBC Sport

    Rob Heap explains how algorithm-based recommendations are saving time in production

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  2. 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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  3. Building a WebAssembly Runtime for BBC iPlayer and enhanced audience experiences

    Juliette Carter

    Research Engineer, BBC R&D

    Building a WebAssembly Runtime for BBC iPlayer and enhanced audience experiences

    How WebAssembly is being rolled out to different BBC platforms.

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  4. The complexities of creating a new 'follow topic' capability

    Dave Lee

    Senior Architect, BBC Home

    The complexities of creating a new 'follow topic' capability

    The background to creating a 'follow' functionality for BBC topics.

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  5. Me, you and the machine

    Matthew Postgate

    Chief Technology and Product Officer, BBC D&E

    The BBC's Chief Technology and Product Officer explains how the corporation can benefit from Machine Learning.

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  6. How metadata will drive content discovery for the BBC online

    Jonathan Murphy and Jeremy Tarling

    Digital Publishing, Design & Engineering

    How metadata will drive content discovery for the BBC online

    How metadata will be at the heart a new content discovery strategy.

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  7. 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 BBC's digital content.

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  8. Scaling responsible machine learning at the BBC

    Gabriel Straub

    Head of Data Science and Architecture, BBC D&E

    How the BBC's public service principles are being applied to machine learning.

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  9. Navigating the data ecosystem technology landscape

    Hannes Ricklefs, Max Leonard

    BBC Design and Engineering

    Navigating the data ecosystem technology landscape

    The challenges of creating an open and transparent data ecosystem for the BBC.

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  10. Machine learning and editorial collaboration within the BBC

    Anna McGovern, Ewan Nicolson, Svetlana Videnova

    Datalab team

    Machine learning and editorial collaboration within the BBC

    Datalab team members explain how the best machine learning results will come from a multi-disciplined approach.

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