Modeling as framework for knowledge acquisition methodologies and tools
Knowledge acquisition as modeling
Knowledge engineering: principles and methods
Data & Knowledge Engineering - Special jubilee issue: DKE 25
Knowledge engineering and management: the CommonKADS methodology
Knowledge engineering and management: the CommonKADS methodology
Knowledge entry as the graphical assembly of components
Proceedings of the 1st international conference on Knowledge capture
Towards the Semantic Web: Ontology-driven Knowledge Management
Towards the Semantic Web: Ontology-driven Knowledge Management
An introduction to description logics
The description logic handbook
Conceptual modeling with description logics
The description logic handbook
Constraint graphs: a concept map meta-language
Constraint graphs: a concept map meta-language
Ontology as a Requirements Engineering Product
RE '03 Proceedings of the 11th IEEE International Conference on Requirements Engineering
Multiagent Systems for Manufacturing Control
Multiagent Systems for Manufacturing Control
Knowledge engineering and psychology: Towards a closer relationship
International Journal of Human-Computer Studies
Involving Domain Experts in Authoring OWL Ontologies
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
Natural Language Processing with Python
Natural Language Processing with Python
Evaluating ontologies: Towards a cognitive measure of quality
Information Systems
Towards open ontology learning and filtering
Information Systems
An approach for selecting seed URLs of focused crawler based on user-interest ontology
Applied Soft Computing
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A method is proposed to be used as the first step in the ontology acquisition process. This method is based on the use of concept maps as a means of expression for the expert, followed by an application that assists the expert in detailing the structure of the knowledge represented in the map. This application analyses the concept map, taking into account the map topology and key words used by the expert. From this analysis a series of questions are presented to the expert that, when answered, reduce the map ambiguity and identify some common patterns in ontological representations, such as generalizations and mereologic relations. This information can be used by the knowledge engineer during further knowledge acquisition sessions or to direct the expert to a further improvement of the map. The method was tested by a group of volunteers, most of them engineers working at the aerospace sector, and the results suggest that both the use of concept mapping as well as the refining step are acceptable from the point of view of the end user, supporting the claim that this method is viable as an option to reduce some of the difficulties in large scale ontology construction.