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Tech Report kmi-00-04 Abstract


Multivariate Clustering by Dynamics
Techreport ID: kmi-00-04
Date: 2000
Author(s): Marco Ramoni, Paola Sebastiani and Paul Cohen
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We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a time series is approximated by a first order Markov Chain and the overall joint distribution of the variables is simplified by conditional independence assumptions. The algorithm searches for the most probable set of clusters given the data using a entropy-based heuristic search method. The algorithm is evaluated on a set of multivariate time series of propositions produced by the perceptual system of a mobile robot. 1. Knowledge Media Institute, The Open University 2. Department of Mathematics, Imperial College of Science, Technology and Medicine 3. Department of Computer Science, University of Massachusetts at Amherst.

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Also in Proceedings of the 2000 National Conference on Artificial Intelligence (AAAI-2000), Morgan Kaufman, San Mateo, CA, 2000.
 
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Future Internet is...


Future Internet
With over a billion users, today's Internet is arguably the most successful human artifact ever created. The Internet's physical infrastructure, software, and content now play an integral part of the lives of everyone on the planet, whether they interact with it directly or not. Now nearing its fifth decade, the Internet has shown remarkable resilience and flexibility in the face of ever increasing numbers of users, data volume, and changing usage patterns, but faces growing challenges in meetings the needs of our knowledge society. Globally, many major initiatives are underway to address the need for more scientific research, physical infrastructure investment, better education, and better utilisation of the Internet. Within Japan, USA and Europe major new initiatives have begun in the area.

To succeed the Future Internet will need to address a number of cross-cutting challenges including:

  • Scalability in the face of peer-to-peer traffic, decentralisation, and increased openness

  • Trust when government, medical, financial, personal data are increasingly trusted to the cloud, and middleware will increasingly use dynamic service selection

  • Interoperability of semantic data and metadata, and of services which will be dynamically orchestrated

  • Pervasive usability for users of mobile devices, different languages, cultures and physical abilities

  • Mobility for users who expect a seamless experience across spaces, devices, and velocities