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Comparing Ontologies Using Multi-agent System and Knowledge Base
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.ORCID iD: 0000-0002-9255-9236
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS.
2010 (English)In: KNOWLEDGE-BASED AND INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS / [ed] Setchi R; Jordanov I; Howlett RJ; Jain LC, 2010, Vol. 6279, 124-134 p.Conference paper (Refereed)
Abstract [en]

This paper presents an approach for handling several ontologies in a domain by integrating a knowledge base in a multi-agent system. For some online facilities, like e-business, several ontologies in different languages are needed to match the users' request. Finding the ontologies is one of the tasks, comparing and combining these ontologies is the other. The accomplishment of these tasks depends on the content in the ontologies like tags and structure but, in some cases, also language and matching techniques. Matching the contents is difficult due to differences between ontologies, often resulting from the lack of explicit and exact standards and development guidelines. This complication increases with the ontologies diverged languages. These problems are tackled by applying a multi-agent system wherein the agents, i.e., software agents and meta-agents, use the users' request to search for ontologies and the knowledge base to compare and combine the contents of the ontologies to create an overall solution. The software agents search for ontologies; the meta-agents keep track of the software agents, ontologies and the knowledge base that reasons with the contents of the ontologies.

Place, publisher, year, edition, pages
2010. Vol. 6279, 124-134 p.
, Lecture Notes in Artificial Intelligence, ISSN 0302-9743 ; 4
Keyword [en]
Multi-agent systems, Software Agents, Meta-agents, Ontologies, Knowledge bases, Reasoning
National Category
Computer and Information Science
URN: urn:nbn:se:kth:diva-33477ISI: 000289445700014ScopusID: 2-s2.0-78649257725ISBN: 978-3-642-15383-9OAI: diva2:417195
14th Interntional Conference on Knowledge-Based and Intelligent Information and Engineering Systems
QC 20110516Available from: 2011-05-16 Created: 2011-05-09 Last updated: 2011-05-16Bibliographically approved

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