An ontology typically provides a vocabulary describing a domain of interest and a
specification of the meaning of terms in that vocabulary. Depending on the precision of this …

There are three main drawbacks of current evolutionary approaches for determining the
weights of ontology matching system. The first drawback is that it is difficult to simultaneously …

Instance coreference resolution is an essential problem in studying semantic web, and it is
also critical for the implementation of web of data and future integration and application of …

Sensor ontology is able to resolve the sensor data heterogeneity issue among the Cybertwin-
driven 6G based Internet of Everything (IoE) systems. However, due to human subjectivity …

Modern infrastructures for information and communication technologies are aimed at
providing enhanced services by integrating the knowledge spread on the web through an …

Data heterogeneity is the obstacle for the resource sharing on Semantic Web (SW), and
ontology is regarded as a solution to this problem. However, since different ontologies are …

Biomedical ontology is a unified model for describing biomedical knowledge, which can be
of help to solve the issues of heterogeneity in different biomedical databases. However, the …

With the proliferation of sensors, semantic web technologies are becoming closely related to
sensor network. The linking of elements from semantic web technologies with sensor …

To support semantic inter‐operability between the biomedical information systems, it is
necessary to determine the correspondences between the heterogeneous biomedical …

Ontologies are recognized as a fundamental component for enabling interoperability across
heterogeneous systems and applications. Indeed, they try to fit a common understanding of …