The major challenge in mining data streams is the issue of concept drift, the tendency of the underlying data generation process to change over time. In this paper, we propose a g...
We address the problem of content-based dissemination of highly-distributed, high-volume data streams for stream-based monitoring applications and large-scale data delivery. Exist...
We recall the basic idea of an algebraic approach to learning Bayesian network (BN) structures, namely to represent every BN structure by a certain (uniquely determined) vector, c...
Integration over a domain, such as a Euclidean space or a Riemannian manifold, is a fundamental problem across scientific fields. Many times, the underlying domain is only acces...
In this paper we present a uni ed approach for delivering hypermedia/multimedia objects over broadband networks. Documents are stored in various multimedia servers, while the inli...
Christos Bouras, Vaggelis Kapoulas, D. Miras, Vagg...