Data-driven personalisation of television content: a survey

被引:0
|
作者
Lyndon Nixon
Jeremy Foss
Konstantinos Apostolidis
Vasileios Mezaris
机构
[1] MODUL Technology,
[2] Birmingham City University,undefined
[3] CERTH-ITI,undefined
来源
Multimedia Systems | 2022年 / 28卷
关键词
Broadcasting; Data-driven TV; Deep learning; Media analysis; Media annotation; Personalisation; Recommendation;
D O I
暂无
中图分类号
学科分类号
摘要
This survey considers the vision of TV broadcasting where content is personalised and personalisation is data-driven, looks at the AI and data technologies making this possible and surveys the current uptake and usage of those technologies. We examine the current state-of-the-art in standards and best practices for data-driven technologies and identify remaining limitations and gaps for research and innovation. Our hope is that this survey provides an overview of the current state of AI and data-driven technologies for use within broadcasters and media organisations. It also provides a pathway to the needed research and innovation activities to fulfil the vision of data-driven personalisation of TV content.
引用
收藏
页码:2193 / 2225
页数:32
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