Enriching Domain Ontologies with Knowledge-based Semantics
Serdica Journal of Computing, Tome 13 (2019) no. 3-4, pp. 107-122.

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Association rules and ontologies are both domain-based knowledge. However, the first is unexpected discovered knowledge from databases, while the second is a priori knowledge. In this paper, based on a generic meta-schema as a common referential and theoretical foundation, we show how a set of computed and pruned association rules can be useful in enriching a domain ontology. To this end, the meta- schema is scanned with the itemsets appearing in each association rule. Then, according to the formal links between the concepts or the attributes involved, a semantic-based check constraint is built. As a result, the ontology and the database are continuously tuned with new semantics. ACM Computing Classification System (1998): D.2.1, H.2.8, K.6.1.
Keywords: Association Rules, Relational Database, Ontology, UML
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Sy, Oumar. Enriching Domain Ontologies with Knowledge-based Semantics. Serdica Journal of Computing, Tome 13 (2019) no. 3-4, pp. 107-122. http://geodesic.mathdoc.fr/item/SJC_2019_13_3-4_a1/