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2005 | nr 1064 Pozyskiwanie wiedzy i zarządzanie wiedzą | 339--350
Tytuł artykułu

Wnioskowanie na podstawie wiedzy wyrażonej ontologicznie - koncepcja środowiska

Warianty tytułu
Concept of Environment for Reasoning on Basis of Knowledge Expressed Using Ontologies
Języki publikacji
PL
Abstrakty
Omówiono znaczenie ontologii-terminu zaczerpniętego z filozofii, w kontekście opisu danych znajdujących się w sieci. Przedstawiono wybrane metody łączenia ontologii, podkreślając, iż ontologie umożliwiają współdzielenie wiedzy. Na koniec omówiono wnioskowanie i architekturę systemu do zarządzania wiedzą zapisaną w postaci ontologii.
EN
Classical approach to reality modelling in databases causes difficulties in development of model of represented data as well as integration of data stored in different, heterogeneous and distributed systems. It lacks of common representation methods of data and their semantics as well as methods of data exchanging among sources, and in consequence - knowledge obtained on their basis. The need of the introduction of standards to knowledge descriptions came into being. One of the intensely developing approaches are ontologies. Ontologies make it possible to model a reality using concepts, their properties and relationships among them. Knowledge based on ontologies may also contain the set of instances of concepts defined in such a way. Several ontology description languages were proposed (for example Ontolingua, OIL, DAML). Currently, commonly used are RDF, RDFS and OWL (the standards of description of these languages were prepared and accepted by W3C). Ontologies provide concepts which may be understood in the same way by all the systems operating on the knowledge represented in this manner. They make it possible to share knowledge and to realize cooperation between different knowledge sources. It is possible to develop an ontology structure performing the integration process, assuming that ontologies contain only partial descriptions of some concepts and may be complementary to one another. As a result one can obtain a model of reality with higher expression. Ontology integration may be performed using tools like library Jena or Prompt - a plug-in to ontologies editor Protégé 2000. Such a knowledge organization provides environment for performing reasoning process. Reasoning may use distributed knowledge from particular sources containing knowledge expressed in ontologies. There exist several solutions making it possible to perform a reasoning process using ontological representation (in OWL or other compatible to Protégé 2000 format): Racer, F-OWL with Flora2, Bossam, Jess, and Algernon. The most interesting and promising approach is Description Logic reasoning. In the paper, a concept of a system which makes it possible to reason on the basis of distributed sources of medical knowledge, expressed in RDF or OWL, is presented. One can distinguish the following logical layers: knowledge sources using ontological representation, a knowledge integration layer (based on agent approach, supported by JADE platform), a reasoning layer using Racer system and a user interaction layer (responsible for queries about knowledge, among the others the ones which need a reasoning process). (original abstract)
Twórcy
Bibliografia
  • Algernon - Rule-Based Programming, http://algernon-j.sourceforge.net/.
  • Bossam - A Java-based Rule Processor for the Semantic Web, http://mknows.etri.re.kr/bossam.
  • Donini P.M., Lenzerini M., Nardi D., Schaerf A., Reasoning in Description Logic, A Great Collection, red. U. Gnowho, CLSI Publications, 1997.
  • F-OWL: An OWL Inference Engine in Flora-2, http://fowl.sourceforge.net/.
  • Fridman N., Musen M., SMART: Automated Support for Ontology Merging and Alignment, Twelth Workshop on Knowledge Acquisition, Modeling, and Management, Banff, Canada 1999.
  • Java Agent Development Framework, http://jade.cselt.it/.
  • JENA - A Semantic Web Framework for Java, http://jena.sourceforge.net/index.html.
  • JESS (tm), the Rule Engine for the Java(tm) Platform, http://herzberg.ca.sandia.gov/jess/.
  • Koźlak J., Zygmunt A., Zaawansowane metody reprezentacji wiedzy z wybranego obszaru medycyny, [w:] Współczesne problemy sieci komputerowych. Zastosowanie i bezpieczeństwo, red. A. Kwiecień, A. Grzywak, Wydawnictwo Naukowo-Techniczne, Warszawa, Gliwice 2004.
  • Manola F., Miller E., RDF Primer, W3C Recommendation, http://www.w3.org/TR/2004/REC-rfd-primer-20040210.
  • McGuinness D.L., Harmelen F., OWL. Web Ontology Language. Overview, W3C Recommendation, http://www.w3.org/TR/2004/REC-owl-features-20040210, 2004.
  • Nardi D., Brachman R.J., An Introduction to Description Logic, [w:] red. F. Baader, D. Calva-nese, D. McGuinness, D. Nardi, P. Patel-Schneider Description Logic Handbook, Theory, Implementation and Applications, Cambridge University Press, 2003.
  • Noy N.F., McGuinness D.L., Ontology Development 101: A Guide to Creating Your First Ontology, SMI Tech. Report, SMI-2001-0880.
  • Noy N.F., Musen M.A., The PROMPT Suite: Interactive Tools For Ontology Merging And Mapping, "International Journal of Human-Computer Studies", 2003.
  • Pinto H.S., Gomez-Perez A., Martins J.P., Some Issues on Ontology Integration, Proceedings of IJCAI99 Workshop on Ontologies and Problem Solving Methods: Lessons Learned and Future Trends, Stokholm, Sweden, 1999.
  • Protege OWL Plugin, http://protege.stanford.edu/plugins/owl/.
  • Resource Description Framework (RDF), http://www.w3.org/RDF.
  • Sowa J.F., Ontology, Metadata, and Semiotics, [w:] Conceptual Structures: Logical, Linguistic, and Computational Issues, Lecture Notes in AI
Typ dokumentu
Bibliografia
Identyfikatory
Identyfikator YADDA
bwmeta1.element.ekon-element-000093067588

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