Available domain ontologies are increasing over the time. However there is a huge amount of data stored and managed with RDBMS. We propose a method for learning association rules from both sources of knowledge in an integrated way. The extracted patterns can be used for performing: data analysis, knowledge completion, ontology refinement.

Semantic Knowledge Discovery from Heterogeneous Data Sources

Bryl, Volha;Serafini, Luciano
2012

Abstract

Available domain ontologies are increasing over the time. However there is a huge amount of data stored and managed with RDBMS. We propose a method for learning association rules from both sources of knowledge in an integrated way. The extracted patterns can be used for performing: data analysis, knowledge completion, ontology refinement.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11582/83407
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