Supervised classification methods have been shown to be very effective for a large number of applications. They require a training data set whose instances are labeled to indicate...
In this paper, we present a stream-based mining algorithm for online anomaly prediction. Many real-world applications such as data stream analysis requires continuous cluster opera...
The issue of data mining in time series databases is of utmost importance for many practical applications and has attracted a lot of research in the past years. In this paper, we ...
Emerging application domains such as interactive vision, animation, and multimedia collaboration display dynamic scalable parallelism, and high computational requirements, making ...
The Ambient Intelligence (AmI) paradigm requires a robust interpretation of people actions and behaviour and a way for automatically generating persistent spatial-temporal models o...