Tech Reports
Tech Report kmi-06-08 Abstract
Probabilistic Methods for Data Integration in a Multi-Agent Query Answering System
Techreport ID: kmi-06-08
Date: 2006
Author(s): Miklos Nagy, Maria Vargas-Vera, Enrico Motta
This report describes a proposal for a multi agent ontology-mapping framework that makes use of probabilistic information in order to enhance the correctness of the mapping. The proposed research focuses on two correlated areas namely similarity measures with its representation as a Dempster-Shafer belief function and usability of different optimalisation methods for combining these belief functions in a distributed environment. The main goal of our proposed research is to establish a multi agent framework that integrates user query related information from distributed scientific databases utilizing the AQUA system. The outcome of the research will contribute to the feasibility study of a distributed information integration network that is based on the European Commission Joint Research Centers data management and dissemination databases (AlloysDB, GasketDB, CorrosionDB, HTR-FUELDB), which stores mechanical and physical properties of engineering materials produced by the European RTD projects. These databases cover the materials behavior at low, elevated and high temperatures for base materials and welded joints and also includes irradiation materials testing in the field of fusion and fission and thermal barrier coatings tests for gas turbines.
Future Internet
KnowledgeManagementMultimedia &
Information SystemsNarrative
HypermediaNew Media SystemsSemantic Web &
Knowledge ServicesSocial Software
Social Software is...

Interacting with other people not only forms the core of human social and psychological experience, but also lies at the centre of what makes the internet such a rich, powerful and exciting collection of knowledge media. We are especially interested in what happens when such interactions take place on a very large scale -- not only because we work regularly with tens of thousands of distance learners at the Open University, but also because it is evident that being part of a crowd in real life possesses a certain 'buzz' of its own, and poses a natural challenge. Different nuances emerge in different user contexts, so we choose to investigate the contexts of work, learning and play to better understand the trade-offs involved in designing effective large-scale social software for multiple purposes.
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