Abstract
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.
Highlights
With the wide range of applications and distribution of wireless communication systems, especially about the fifthgeneration (5G) networks, the update speed technology in the Internet of things (IoT) is advancing by leaps and bounds [1, 2]
Different from the previous ontology meta-matching technology used by Xue et al [52, 53], the ontology alignment extraction technology using debate mechanism (DM) considers the matching opinions of each basic matcher to each mapping, so as to output the final alignment
The sensor ontology extracting approach is aimed at finding high-quality alignment from various sensor ontology alignments, which can be used to bridge the semantic gap between heterogeneous sensor ontologies and integrate the knowledge defined inside
Summary
With the wide range of applications and distribution of wireless communication systems, especially about the fifthgeneration (5G) networks, the update speed technology in the Internet of things (IoT) is advancing by leaps and bounds [1, 2]. Plenty of techniques about machine learning have been proposed to determine the optimal aggregating weights for the matchers [23,24,25,26,27,28,29], the catch is that they pay little attention to the effects engendered by each entity mapping’s preferences on different matchers, which decreases the quality of ontology alignment [30]. To overcome this drawback, this work proposes a novel sensor ontology alignment extracting method based on debating mechanism (DM) [31]. The rest of the paper is arranged as follows: Section 2 introduces the related concepts of sensor ontology and ontology alignment extraction; Section 3 describes in details the DM-based ontology alignment extracting method with global and local factors; Section 4 externalizes the experimental results and makes the corresponding analysis; Section 5 draws the conclusion
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