Aligning two representations of the same domain with different expressiveness is a crucial topic in nowadays semantic web and big data research. OWL ontologies and Entity Relation Diagrams are the most widespread representations whose alignment allows for semantic data access via ontology interface, and ontology storing techniques. The term ""alignment" encompasses three different processes: OWL-to-ERD and ERD-to-OWL transformation, and OWL-ERD mapping. In this paper an innovative statistical tool is presented to accomplish all the three aspects of the alignment. The main idea relies on the use of a HMM to estimate the most likely ERD sentence that is stated in a suitable grammar, and corresponds to the observed OWL axiom. The system and its theoretical background are presented, and some experiments are reported.
Pipitone, A., Anastasio, F., Pirrone, R. (2016). An Innovative Statistical Tool for Automatic OWL-ERD Alignment. In 2016 IEEE Tenth International Conference on Semantic Computing (ICSC) (pp.96-99). IEEE [10.1109/ICSC.2016.22].
An Innovative Statistical Tool for Automatic OWL-ERD Alignment
PIPITONE, Arianna;ANASTASIO, Francesca;PIRRONE, Roberto
2016-01-01
Abstract
Aligning two representations of the same domain with different expressiveness is a crucial topic in nowadays semantic web and big data research. OWL ontologies and Entity Relation Diagrams are the most widespread representations whose alignment allows for semantic data access via ontology interface, and ontology storing techniques. The term ""alignment" encompasses three different processes: OWL-to-ERD and ERD-to-OWL transformation, and OWL-ERD mapping. In this paper an innovative statistical tool is presented to accomplish all the three aspects of the alignment. The main idea relies on the use of a HMM to estimate the most likely ERD sentence that is stated in a suitable grammar, and corresponds to the observed OWL axiom. The system and its theoretical background are presented, and some experiments are reported.File | Dimensione | Formato | |
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