A Systematic Review on Knowledge Graphs Classification and Their Various Usages
DOI:
https://doi.org/10.37256/aie.4220233605Keywords:
knowledge graph, knowledge classification, information extraction, knowledge graph construction, entity extraction, relationship extractionAbstract
A Knowledge Graph is a directive graph where the nodes state the entities and the edges describe the relationships between the entities of data. It is also referred to as a Semantic Network. The massive amount of data generated every day can be transformed into knowledge via knowledge graphs for the effective use of these data. Knowing the classification of Knowledge Graphs is required to adapt to different requirements of Knowledge Graphs. Knowledge Graphs are primarily classified concerning their building techniques and their usages. In building techniques, it is considered how the Knowledge Graph is built. For example, the graph can be constructed as a triplet, quadruplet, etc., or created from structured data, e.g., database, or unstructured data, e.g., text, image, etc. On the other hand, Knowledge Graphs can be used for various purposes. For example, Knowledge Graphs can be used for Information Retrieval, Semantic Query, etc., or different types of data visualization. Nowadays, Knowledge Graph is one of the trending topics in the modern technology-dependent world. However, clear and specific discussions on the classifications of Knowledge Graphs and their various usages are less available. In this paper, we will describe the classification of knowledge graphs and their various usages in detail so that the readers can get a clear concept of this topic.