Tech Reports
Tech Report kmi-98-08 Abstract
Bayesian Methods for Intelligent Data Analysis
Techreport ID: kmi-98-08
Date: 1998
Author(s): Marco Ramoni and Paola Sebastiani
This paper provides an introduction to Bayesian statistics as methodological tool for intelligent data analysis, knowledge discovery, and machine learning. The paper starts from the basic concepts of Bayesian statistics and reaches the presentation of most recent developments of the field, such as Bayesian Belief Networks. Knowledge of basic statistical concepts is required. 1. Knowledge Media Institute, The Open University. 2. Department of Statistics, The Open University.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Future Internet is...

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
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