Abstract
Utilizing ontologies enables the sharing and reuse of knowledge within specific domains. However, developing an ontology from scratch is a time-consuming and error-prone task. This necessitates an approach that simplifies the intricate process by utilizing existing resources. In this study, we introduce an improved method for learning OWL ontology from a NoSQL database, specifically MongoDB. Our approach, grounded in Formal Concept Analysis and a set of mapping rules, automates the generation of a comprehensive ontology from complex NoSQL databases. The process involves three key phases: (1) constructing a Formal Context from MongoDB, (2) employing formal concept analysis to derive a concept lattice from the created context, and (3) transforming the concept lattice into an initial ontology representation. We have validated the efficacy of our proposed learning rules through practical application.
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Elguerraoui, E., Boutkhoum, O. (2024). Crafting OWL Ontologies from MongoDB: A Formal Concept Analysis (FCA) Approach. In: Ezziyyani, M., Kacprzyk, J., Balas, V.E. (eds) International Conference on Advanced Intelligent Systems for Sustainable Development (AI2SD'2023). AI2SD 2023. Lecture Notes in Networks and Systems, vol 930. Springer, Cham. https://doi.org/10.1007/978-3-031-54318-0_25
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DOI: https://doi.org/10.1007/978-3-031-54318-0_25
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