Publication | Open Access
Integrating Sensor Ontologies with Global and Local Alignment Extractions
57
Citations
36
References
2021
Year
Sensor Ontology AlignmentOntology MatchingOntology (Information Science)EngineeringAdvanced OntologyOntology EngineeringSemanticsSemantic WebOntology MergingData ScienceManagementData IntegrationInternet Of ThingsOntology AlignmentOntology FusionSensor OntologiesSemantic Sensor NetworkOntology DesignData Modeling
In order to enhance the communication between sensor networks in the Internet of things (IoT), it is indispensable to establish the semantic connections between sensor ontologies in this field. For this purpose, this paper proposes an up‐and‐coming sensor ontology integrating technique, which uses debate mechanism (DM) to extract the sensor ontology alignment from various alignments determined by different matchers. In particular, we use the correctness factor of each matcher to determine a correspondence’s global factor, and utilize the support strength and disprove strength in the debating process to calculate its local factor. Through comprehensively considering these two factors, the judgment factor of an entity mapping can be obtained, which is further applied in extracting the final sensor ontology alignment. This work makes use of the bibliographic track provided by the Ontology Alignment Evaluation Initiative (OAEI) and five real sensor ontologies in the experiment to assess the performance of our method. The comparing results with the most advanced ontology matching techniques show the robustness and effectiveness of our approach.
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