Learning from data streams is a research area of increasing importance. Nowadays, several stream learning algorithms have been developed. Most of them learn decision models that c...
We hypothesize that the variance in volume of high-velocity queries over time can be explained by observing that these queries are formulated in response to events in the world tha...
Monitoring predefined patterns in streaming time series is useful to applications such as trend-related analysis, sensor networks and video surveillance. Most current studies on s...
Yueguo Chen, Mario A. Nascimento, Beng Chin Ooi, A...
Data Stream Management Systems (DSMS) operate under strict performance requirements. Key to meeting such requirements is to efficiently handle time-critical tasks such as managing...
Irina Botan, Gustavo Alonso, Peter M. Fischer, Don...
Monitoring movement of high-dimensional points is essential for environmental databases, geospatial applications, and biodiversity informatics as it reveals crucial information ab...
Michalis Potamias, Kostas Patroumpas, Timos K. Sel...