In this project, we seek to develop and demonstrate a platform for personalized television news to replace the traditional one-broadcast-fits-all model. We forecast that next-generation video news consumption will be more personalized, device agnostic, and pooled from many different information sources. The technology for our project represents a major step in this direction, providing each viewer with a personalized newscast with stories that matter most to them. We believe that such a model can provide a vastly superior user experience and provide fine-grained analytics to content providers. While personalized viewing is increasingly popular for text-based news, personalized real-time video news streams are a critically missing technology.
