The MUSED project seeks to solve challenges in event detection and prediction in multi-source data streams in the context of Big Data.
MUSED aims at developing the framework and techniques necessary for effective and efficient detection and prediction of events from multiple and possibly heterogeneous streaming data sources. We expect to provide contributions on the following research topics:
- Efficient and effective information analysis techniques that are able to detect and predict events in real-time when the sources of data come from multiple and heterogeneous streams.
- Efficient algorithms and structures for indexing and storage to support highly scalable multi-source event detection and prediction.
Learn more about the MUSED project.