Abstract
With the development of the Internet of Things, sensor ontologies have been applied to a variety of fields. Most sensor ontologies are currently built for applications in specific domains, and these ontologies are usually heterogeneous, making it difficult to share or reuse knowledge and concepts. The ontology association methods can be used to construct the semantic mapping between heterogeneous ontologies, so as to effectively determine the similarity between concepts in the ontologies. However, most of the contemporary methods do not make full use of the information that is stored in ontologies and are insufficient for the effective association. This paper proposes a novel association method based on comprehensive similarity. In our proposed method, we first use How-Net to obtain concept representation and calculate the semantic similarity of ontology concepts through sememe Tree and sememe Hierarchy. Then we calculate the structural similarity by the internal structure and the hierarchical relationship between the ontologies and remove the conceptual pairs with low relevance. Finally, we combine the semantic similarity and structural similarity to calculate the similarity matrix between ontology concepts to achieve association. The experimental results on real data show that our method can effectively associate sensor data with domain ontology by combining two different similarity calculation methods.
Highlights
In the past few decades, more IoT (Internet of Things) applications [1], sensor data-based software [2], and social network applications [3] have been generating data
In order to verify that our proposed method of combining semantic similarity and structural similarity can be effectively applied to ontology mapping tasks, we have experimented with semantic reasoning cases in berth management
We will calculate the similarity between the seven concepts in the domain ontology and the nine concepts in the sensor ontology to test whether our method can accurately associate sensor data with domain ontology
Summary
In the past few decades, more IoT (Internet of Things) applications [1], sensor data-based software [2], and social network applications [3] have been generating data. The presence of the ontology improves this situation. On the basis of the World Wide Web, the Semantic Web was proposed, which adds semantic information that machines can understand for various documents, so that there is a semantic association between Web documents, making it an intelligent network. The construction of the Semantic Web involves several critical technologies, and the ontology is one of them. The concept of ontology first appeared in the field of philosophy, which studied whether a noun represented a real entity or a concept. In the 1970s and 1980s, with the development of artificial intelligence, the ontology was introduced into the computer field. The ontology builds models based on a specific category system to express concepts, entities, attributes, relationships, and so on. Ontology is a formal representation of a set of important concepts in a particular domain
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