Internet-distributed television: cultural, industrial and policy dynamics. This project aims to investigate the impact of global subscription video-on-demand platforms on national television markets. The rise of subscription video streaming has created significant challenges for Australian and international broadcast, media and cultural policy frameworks, which are struggling to keep up with audience viewing practices. This project will provide a comparative analysis of how governments are respo ....Internet-distributed television: cultural, industrial and policy dynamics. This project aims to investigate the impact of global subscription video-on-demand platforms on national television markets. The rise of subscription video streaming has created significant challenges for Australian and international broadcast, media and cultural policy frameworks, which are struggling to keep up with audience viewing practices. This project will provide a comparative analysis of how governments are responding and investigating the implications for debates about local content, local screen production, and media diversity. The project will provide an analysis of original production and programming strategies to identify new forms of trans-national media flow. The project will advance an understanding of media globalisation and provide media regulators options and opportunities for a convergent media policy environment.Read moreRead less
Short Sequence Representation Learning with Limited Supervision . Predicting events based on short text and video data is widely found in real-world applications such as online crime detection, cyber-attack identification, and public security protection. However, to develop such an effective prediction model is very difficult due to the problems such as limited supervision, heterogeneous multiple sources, and missing and low-quality data. This project is to tackle these challenges. Expected outc ....Short Sequence Representation Learning with Limited Supervision . Predicting events based on short text and video data is widely found in real-world applications such as online crime detection, cyber-attack identification, and public security protection. However, to develop such an effective prediction model is very difficult due to the problems such as limited supervision, heterogeneous multiple sources, and missing and low-quality data. This project is to tackle these challenges. Expected outcome of this project will lay a theoretical foundation for effective short sequence representation learning and build next-generation intelligent systems. This should benefit our society and economy through the applications of multimodality-integrated video technologies for cybersecurity and public safety. Read moreRead less