Abstract
Ontologies provide shared and reusable pieces of knowledge about a specific domain. Building an ontology by hand is a very hard and prone to errors task. Ontology learning from existing resources provides a good solution to this issue. Databases are widely used to store data. They were often considered as the most reliable sources for knowledge extraction. NOSQL databases are more and more used to store data. MongoDB database is emerging as the fastest growing NOSQL database in the world. It belongs to the document oriented databases variant. This paper proposes an approach to learn OWL ontology from data in MongoDB database and describes a tool implementing transformation rules.
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Abbes, H., Gargouri, F. (2017). M2Onto: An Approach and a Tool to Learn OWL Ontology from MongoDB Database. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_60
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