TY - JOUR
T1 - AI and data-driven media analysis of TV content for optimised digital content marketing
AU - Nixon, Lyndon
AU - Apostolidis, Konstantinos
AU - Apostolidis, Evlampios
AU - Galanopoulos, Damianos
AU - Mezaris, Vasileios
AU - Philipp, Basil
AU - Bocyte, Rasa
PY - 2024/1/19
Y1 - 2024/1/19
N2 - To optimise digital content marketing for broadcasters, the Horizon 2020 funded ReTV project developed an end-to-end process termed “Trans-Vector Publishing” and made it accessible through a Web-based tool termed “Content Wizard”. This paper presents this tool with a focus on each of the innovations in data and AI-driven media analysis to address each key step in the digital content marketing workflow: topic selection, content search and video summarisation. First, we use predictive analytics over online data to identify topics the target audience will give the most attention to at a future time. Second, we use neural networks and embeddings to find the video asset closest in content to the identified topic. Third, we use a GAN to create an optimally summarised form of that video for publication, e.g. on social networks. The result is a new and innovative digital content marketing workflow which meets the needs of media organisations in this age of interactive online media where content is transient, malleable and ubiquitous.
AB - To optimise digital content marketing for broadcasters, the Horizon 2020 funded ReTV project developed an end-to-end process termed “Trans-Vector Publishing” and made it accessible through a Web-based tool termed “Content Wizard”. This paper presents this tool with a focus on each of the innovations in data and AI-driven media analysis to address each key step in the digital content marketing workflow: topic selection, content search and video summarisation. First, we use predictive analytics over online data to identify topics the target audience will give the most attention to at a future time. Second, we use neural networks and embeddings to find the video asset closest in content to the identified topic. Third, we use a GAN to create an optimally summarised form of that video for publication, e.g. on social networks. The result is a new and innovative digital content marketing workflow which meets the needs of media organisations in this age of interactive online media where content is transient, malleable and ubiquitous.
U2 - 10.1007/s00530-023-01195-7
DO - 10.1007/s00530-023-01195-7
M3 - Article
SN - 0942-4962
VL - 30
JO - Multimedia Systems
JF - Multimedia Systems
IS - 1
M1 - 25
ER -