Autonomous Querying for Knowledge Networks

Authors:
Kieran Greer;Matthias Baumgarten;Chris Nugent;Maurice Mulvenna;Kevin Curran
Affiliations:
School of Computing and Mathematics and Computer Science Research Institute, University of Ulster, Northern Ireland,UK;School of Computing and Mathematics and Computer Science Research Institute, University of Ulster, Northern Ireland,UK;School of Computing and Mathematics and Computer Science Research Institute, University of Ulster, Northern Ireland,UK;School of Computing and Mathematics and Computer Science Research Institute, University of Ulster, Northern Ireland,UK;School of Computing and Intelligent Systems and Computer Science Research Institute, University of Ulster, Northern Ireland,UK
Venue:
ATC '08 Proceedings of the 5th international conference on Autonomic and Trusted Computing
Year:
2008

Citing 12
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Abstract

A knowledge network is a construct that will organise knowledge in a way that allows it to be efficiently retrieved and used. While an Internet-based network is the obvious application area, the system would also be suitable for pervasive sensorised environments. Key elements thereof are its lightweight, reference-based structure and its autonomous nature. This paper is concerned with describing the querying process that will be used to retrieve information from the network. For this process, the network metadata will act as a lightweight and distributed ontology, where the hierarchical structures of the network will describe the main relationships and guide the search. Then, using autonomous querying, the ontology can be updated with personal references between sources, allowing for semantically unrelated concepts to also be linked together. A novel linking mechanism is described that is shown to be effective, dynamic and adaptive, and could be particularly useful in tomorrow's Semantic Web environment.