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Modeling Domain Ontology for Occupational Therapy Resources Using Natural Language Programming (NLP) Technology to Model Domain Ontology of Occupational Therapy Resources

Sawsaa, Ahlam and Lu, Joan (2013) Modeling Domain Ontology for Occupational Therapy Resources Using Natural Language Programming (NLP) Technology to Model Domain Ontology of Occupational Therapy Resources. International Journal of Information Retrieval Research, 3 (4). pp. 104-119. ISSN 2155-6377

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Abstract

Creation and development of a formal domain ontology of Ocuupational Therapy (OT) requires the prescription
and formal evaluation of the results through specific criteria. Methontology of development ontologies was
followed to create OTO ontology, and was implemented by using Protégé- OWL. Accuracy of OTO ontology
was assessed using a set of ontology design cretria. This paper describes a software engineering approach
to model domain ontology for occupational therapy resources (OT) using Natural Language Programming
(NLP) technology. The rules were written to annotate the domain concepts using Java Annotation Patterns
Engine (JAPE) grammar. It is used to support regular expression matching and thus annotate OT concepts
by using the GATE developer tool. This speeds up the time-consuming development of the ontology, which is
important for experts in the domain facing time constraints and high workloads. The rules provide significant
results: the pattern matching of OT concepts based on the lookup list produced 403 correct concepts and the
accuracy was generally higher. Using NLP technique is a good approach to reducing the domain expert’s
work, and the results can be evaluated. This study contributes to the understanding of ontology development
and evaluation methods to address the knowledge gap of using ontology in the decision support system component
of occupational therepy.

Item Type: Article
Subjects: T Technology > T Technology (General)
Schools: School of Computing and Engineering
School of Computing and Engineering > High-Performance Intelligent Computing > Information and Systems Engineering Group
Related URLs:
Depositing User: Ahlam Sawsaa
Date Deposited: 10 Jul 2014 15:26
Last Modified: 14 Nov 2015 12:56
URI: http://eprints.hud.ac.uk/id/eprint/21159

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