A novel approach for learning ontology from relational database: from the construction to the evaluation

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Abstract

The aim of converting relational database into Ontology is to provide applications that are based on the semantic representation of the data. Whereas, representing the data using ontologies has shown to be a useful mechanism for managing and exchanging data. This is the reason why bridging the gap between relational databases and ontologies has attracted the interest of the ontology community from early years, and it is commonly referred to as the database-to-ontology mapping problem. In this paper, we: (1) propose a new life cycle for ontology learning from RDBs based on the software engineering requirements; (2) describe a new method for building ontology from Relational database based on the predefined life cycle; (3) add three new semantics that can be extracted from RDB; (4) we suggest an evaluation process based on two categories of metrics: (i) conceptual ontology (TBox) evaluation metrics; (ii) factual ontology (ABox) evaluation metrics.

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Ben Mahria, B., Chaker, I., & Zahi, A. (2021). A novel approach for learning ontology from relational database: from the construction to the evaluation. Journal of Big Data, 8(1). https://doi.org/10.1186/s40537-021-00412-2

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