Abstract
To obtain runnable knowledge – convertible into executable software – from the highest abstraction level of an application, one should start with a neat set of application ontologies. But the latter are not readily available in the literature. One needs to generate dedicated and smaller application ontologies from larger generic domain ontologies. The main problem to be solved is to optimize the size of the generated application ontologies as a trade-off between two opposing tendencies: to enlarge the selected domain ontology segments to include most relationships between relevant concepts, while reducing the same segments to exclude irrelevant terms. This work describes a chain of algorithms and a series of heuristic rules to reach the proposed solution. Finally, case studies are used to actually illustrate the whole approach.
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Exman, I., Iskusnov, D. (2015). Apogee: Application Ontology Generation with Size Optimization. In: Fred, A., Dietz, J., Aveiro, D., Liu, K., Filipe, J. (eds) Knowledge Discovery, Knowledge Engineering and Knowledge Management. IC3K 2014. Communications in Computer and Information Science, vol 553. Springer, Cham. https://doi.org/10.1007/978-3-319-25840-9_29
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