DocumentCode :
3439690
Title :
Use of ontologies for decision support generation and analysis
Author :
Bodkin, Michael ; Harris, Michelle ; Helton, Alicia
Author_Institution :
Lockheed Martin STS, Orlando, FL
fYear :
2005
fDate :
26-29 Sept. 2005
Firstpage :
684
Lastpage :
689
Abstract :
The purpose of this paper is to illustrate the benefits of using ontologies to generate various artificial intelligence exchange and service tie to all test environments (AI-ESTATE - IEEE Std 1232trade-2002) diagnostic models. One of these benefits is the ability to take engineering information and create multiple models from the same information, thereby reducing the possibility of translation errors. Another benefit offered in the use of an ontology is the ability to determine all possible diagnoses that lead to a particular indictment, thereby making the diagnostic model´s coverage explicit. The ontology will be created using the OWL Web ontology language. The generation of the AI-ESTATE diagnostic models will be based on the use of description logic. Description logic will also be used to perform the coverage analysis
Keywords :
automatic test equipment; decision support systems; ontologies (artificial intelligence); AI-ESTATE diagnostic models; OWL Web ontology language; artificial intelligence exchange; coverage analysis; decision support analysis; decision support generation; description logic; ontologies; service tie; test environments; Artificial intelligence; Automatic testing; Data engineering; Knowledge engineering; Lakes; Logic; OWL; Ontologies; Sociotechnical systems; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Autotestcon, 2005. IEEE
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-9101-2
Type :
conf
DOI :
10.1109/AUTEST.2005.1609218
Filename :
1609218
Link To Document :
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