Using hamming similarity to map ontology learning: a new data mining system
Proceedings of the 2013 Research in Adaptive and Convergent Systems
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In this paper a method is proposed to be used as the first step in the ontology construction process. This method, specially tailored to ontology construction for knowledge management applications, is based on the use of concept maps as a mean of expression for the expert, followed by an application that assists in the capture of the expert intention with the goal of further formalizing 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 is presented to the expert that, when answered, reduce the map ambiguity and identify some common patterns in ontological representations, such as generalizations and mere logic relations. This information could then be used by the knowledge engineer during further knowledge acquisition sessions or to direct the expert to a further formalization or improvement of the map. The method was tested in a group of volunteers, all of them engineers working at the aerospace sector, and the results suggest that both the use of conceptual mapping as well as the intention capture 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.