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 newapproach 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 rationale , Natural Language Processing Tools , Ontology Evaluation , ontology learning , Ontology Reuse