Data-driven personalisation of television content: a survey

被引:2
|
作者
Nixon, Lyndon [1 ]
Foss, Jeremy [2 ]
Apostolidis, Konstantinos [3 ]
Mezaris, Vasileios [3 ]
机构
[1] MODUL Technol, Vienna, Austria
[2] Birmingham City Univ, Birmingham, W Midlands, England
[3] CERTH ITI, Thessaloniki, Greece
基金
欧盟地平线“2020”;
关键词
Broadcasting; Data-driven TV; Deep learning; Media analysis; Media annotation; Personalisation; Recommendation; KEY FRAME EXTRACTION; MULTIMEDIA CLASSIFICATION; TV RECOMMENDATION; VIDEO; SUPERRESOLUTION; SEGMENTATION; ATTENTION; IDENTIFICATION; BROADCAST; GENRE;
D O I
10.1007/s00530-022-00926-6
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
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:33
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