DocumentCode :
2859718
Title :
Enabling Context-Aware Agents to Understand Semantic Resources on The WWWand The Semantic Web
Author :
Huang, Weihong ; Webster, David
Author_Institution :
The University of Hull, UK
fYear :
2004
fDate :
20-24 Sept. 2004
Firstpage :
138
Lastpage :
144
Abstract :
Six years after Tim Berners-Lee and his colleagues drew the vision of the Semantic Web (SW) in 1998, the SW is very likely to take off in the near future based on a set of specifications such as the Resource Description Framework (RDF) and the Web Ontology Language (OWL). As a natural result, people will see the coexistence of the WWW and the SW for a certain long time. Under this situation, how to bridge the gap between the WWW and the SW will become an inevitable issue. In this paper, we present a context-aware approach on enabling agents to understand semantic resources on the two webs. The basic idea of this approach is to structure user-centred contextual information to facilitate agent-based (inter)operations on the network. Based on this idea, we design a Knowledge Interoperation Reference Model (KIRM) to address the interoperation issue at the global level. To demonstrate how agents understand semantic resources in a context-aware manner in real practices, we develop a news aggregation system based on RDF Site Summary / Really Simple Syndication (RSS) using agents. Considering the fact that RSS format set is a combination of XML and RDF, the success of agent understanding of RSS content under specific semantic contexts shows the possibility of extending and applying the context-aware approach in other semantic-based applications on both the WWW and the SW in the future.
Keywords :
Bridges; Computer vision; Engines; HTML; Internet; OWL; Resource description framework; Semantic Web; World Wide Web; XML;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence, 2004. WI 2004. Proceedings. IEEE/WIC/ACM International Conference on
Print_ISBN :
0-7695-2100-2
Type :
conf
DOI :
10.1109/WI.2004.10028
Filename :
1410795
Link To Document :
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