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Automatic ontology creation using adaptation

Published online by Cambridge University Press:  19 May 2009

Valerie Cross  and
Vishal Bathija
Valerie Cross
Affiliation:
Computer Science and Systems Analysis Department, Miami University, Oxford, Ohio, USA
Vishal Bathija
Affiliation:
Planetsoft Holdings, Burlington, Massachusetts, USA
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Abstract

Ontologies are an emerging means of knowledge representation to improve information organization and management, and they are becoming more prevalent in the domain of engineering design. The task of creating new ontologies manually is not only tedious and cumbersome but also time consuming and expensive. Research aimed at addressing these problems in creating ontologies has investigated methods of automating ontology reuse mainly by extracting smaller application ontologies from larger, more general purpose ontologies. Motivated by the wide variety of existing learning algorithms, this paper describes a new approach focused on the reuse of domain-specific ontologies. The approach integrates existing software tools for natural language processing with new algorithms for pruning concepts not relevant to the new domain and extending the pruned ontology by adding relevant concepts. The approach is assessed experimentally by automatically adapting a design rationale ontology for the software engineering domain to a new one for the related domain of engineering design. The experiment produced an ontology that exhibits comparable quality to previous attempts to automate ontology creation as measured by standard content performance metrics such as coverage, accuracy, precision, and recall. However, further analysis of the ontology suggests that the automated approach should be augmented with recommendations presented to a domain expert who monitors the pruning and extending processes in order to improve the structure of the ontology.

Keywords

Design RationaleNatural Language Processing ToolsOntology EvaluationOntology LearningOntology Reuse
Type
Regular Articles
Information
AI EDAM , Volume 24 , Issue 1: Design Computing and Cognition , February 2010 , pp. 127 - 141
Copyright
Copyright © Cambridge University Press 2010

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