publication . Conference object . 2020

Content Adaptation, Personalisation and Fine-grained Retrieval: Applying AI to Support Engagement with and Reuse of Archival Content at Scale

Rasa Bocyte; Johan Oomen;
Open Access
  • Published: 27 Mar 2020
Recent technological advances in the distribution of audiovisual content have opened up many opportunities for media archives to fulfil their outward-facing ambitions and easily reach large audiences with their content. This paper reports on the initial results of the ReTV research project that aims to develop novel approaches for the reuse of audiovisual collections. It addresses the reuse of archival collections from three perspectives: content holders (broadcasters and media archives) who want to adapt audiovisual content for distribution on social media, end-users who have switched from linear television to online platforms to consume audiovisual content and...
Persistent Identifiers
free text keywords: Reuse, Video Summarisation, Content Adaptation, Personalisation, Multimedia Annotation, Retrieval, Multimedia, computer.software_genre, computer, Computer science, Content adaptation, Reuse, Personalization
Funded by
Enhancing and Re-Purposing TV Content for Trans-Vector Engagement
  • Funder: European Commission (EC)
  • Project Code: 780656
  • Funding stream: H2020 | RIA
Validated by funder
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Open Access
Conference object . 2020
Provider: ZENODO
Conference object . 2020
Provider: Crossref
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