Abstract We address the problem of monitoring and identification of correlated burst patterns in multi-stream time series databases. We follow a two-step methodology: first we iden...
A key issue when designing and implementing largescale publish/subscribe systems is how to efficiently propagate subscriptions among the brokers of the system. Brokers require thi...
In this paper, we present a probabilistic framework for automatic detection and tracking of objects. We address the data association problem by formulating the visual tracking as ...
This paper presents an efficient algorithm for learning Bayesian belief networks from databases. The algorithm takes a database as input and constructs the belief network structur...
In high-end grid networks, distributed resources (scientific instruments, CPUs, storages, etc.) are interconnected to support computing-intensive and data-intensive applications, w...