Live video content is increasingly consumed over IP networks in addition to traditional broadcasting. The move to IP provides a huge opportunity to discover what people are watching in much greater breadth and depth than currently possible through interviews or set-top box based data gathering by rating organizations, because it allows direct analysis of consumer behavior via the logs they produce. The ViSTA-TV project proposes to gather consumers’ anonymized viewing behavior and the actual video streams from broadcasters/IPTV-transmitters, to combine them with enhanced electronic program guide information as the input for a holistic live-stream data mining analysis.
ViSTA-TV will employ the gathered information via a stream-analytics process to generate a high-quality linked open dataset (LOD) describing live TV programming. Combining the LOD with the behavioral information gathered, ViSTA-TV will be in the position to provide highly accurate market research information about viewing behavior that can be used for a variety of analyses of high interest to all participants in the TV-industry. ViSTA-TV will employ the information gathered to build a recommendation service that exploits both usage information and personalized feature extraction in conjunction with existing metadata to provide real-time viewing recommendations.
These results will be made possible by scientific progress in data-stream mining consisting of advances in data mining for tagging, recommendations, and behavioral analyses and temporal/probabilistic RDF-triple stream processing.
ViSTA-TV is a European Union-funded research project, beginning on 1 June 2012, and lasting for two years. The partners are:
- University of Zurich (Coordindator)
- TU Dortmund University
- Rapid-I GmbH
- Zattoo Europa AG
- Vrije Universiteit Amsterdam