Tech Reports

Tech Report kmi-00-05 Abstract

Sequence Learning via Bayesian Clustering by Dynamics
Techreport ID: kmi-00-05
Date: 2000
Author(s): Paola Sebastiani, Marco Ramoni and Paul Cohen

This chapter introduces a Bayesian method for clustering dynamic processes. The method models dynamics as Markov chains and then applies an agglomerative clustering procedure to discover the most probable set of clusters capturing different dynamics. To increase efficiency, the algorithm uses an entropy-based heuristic search strategy. When applied to clustering sensor data from mobile robots, the algorithm produces clusters that are meaningful in the domains of application. 1. Department of Mathematics, Imperial College of Science, Technology and Medicine 2. Knowledge Media Institute, The Open University 3. Department of Computer Science, University of Massachusetts at Amherst

Publication(s):

Also in Sequence Learning: Paradigms, Algorithms, and Applications, L. Giles and R. Sun, editors, Springer, New York, NY, 2000.

Future Internet

Knowledge
Management Multimedia &
Information Systems Narrative
Hypermedia New Media Systems Semantic Web &
Knowledge Services

Future Internet is...

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