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

Rasa Bocyte, Johan Oomen

2020

Abstract

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 creatives in the media industry who seek audiovisual content that could be used in new productions. The paper presents three uses cases that demonstrate how AI-based video analysis technologies can facilitate these reuse scenarios through video content adaptation, personalisation and fine-grained retrieval.

Paper Citation

in Harvard Style

Bocyte R. and Oomen J. (2020). Content Adaptation, Personalisation and Fine-grained Retrieval: Applying AI to Support Engagement with and Reuse of Archival Content at Scale. In Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ARTIDIGH, ISBN 978-989-758-395-7, pages 506-511. DOI: 10.5220/0009188505060511

in Bibtex Style

@conference{artidigh20,
author={Rasa Bocyte and Johan Oomen},
title={Content Adaptation, Personalisation and Fine-grained Retrieval: Applying AI to Support Engagement with and Reuse of Archival Content at Scale},
booktitle={Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ARTIDIGH,},
year={2020},
pages={506-511},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009188505060511},
isbn={978-989-758-395-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 12th International Conference on Agents and Artificial Intelligence - Volume 1: ARTIDIGH,
TI - Content Adaptation, Personalisation and Fine-grained Retrieval: Applying AI to Support Engagement with and Reuse of Archival Content at Scale
SN - 978-989-758-395-7
AU - Bocyte R.
AU - Oomen J.
PY - 2020
SP - 506
EP - 511
DO - 10.5220/0009188505060511