Abstract:
A knowledge graph is a data model representing real-world entities and relationships in a machine-readable format providing a comprehensive view of a specific domain or multiple domains. Dynamic ontology is a concept that refers to the idea that the fundamental nature of reality changes over time. Dynamic ontology generation using a knowledge graph automatically creates a new ontology or updates an existing ontology. This process keeps the ontology up-to-date with the changing real-world information. The most important part of dynamic ontology generation is integrating the domain ontology into the knowledge graph and updating the knowledge graph accordingly. The primary purpose of the research is to develop a dynamic environment that integrates the domain ontology with the knowledge graph. The main problem here is the dynamic integration of new data and concepts with changes in real-world information. To achieve this task graph-based ontology mapping framework is developed with matrix-based graph merging, graph clustering, cluster label propagation and matrix-based ontology mapping. The new mapping algorithm was tested with real-time dynamic data and compared with existing systems. The proposed approach outperforms the existing system in accuracy, relevancy and introducing new concepts to the ontology.