A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
Ontology Learning for the Semantic Web
Ontology Learning for the Semantic Web
Design Rationale Systems: Understanding the Issues
IEEE Expert: Intelligent Systems and Their Applications
An overview of methods and tools for ontology learning from texts
The Knowledge Engineering Review
Learning Domain Ontologies from Document Warehouses and Dedicated Web Sites
Computational Linguistics
Software Engineering Using RATionale
Journal of Systems and Software
Deployment of an ontological framework of functional design knowledge
Advanced Engineering Informatics
A framework for handling inconsistency in changing ontologies
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Lexically evaluating ontology triples generated automatically from texts
ESWC'05 Proceedings of the Second European conference on The Semantic Web: research and Applications
Generating ontologies via language components and ontology reuse
NLDB'07 Proceedings of the 12th international conference on Applications of Natural Language to Information Systems
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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.