Generating conceptual subgraph from tabular data for knowledge graph matching

In this paper, we study the problem of analyzing the relationship between data given in a tabular format and a target knowledge graph, e.g., Wikidata. It is most important to find the label that indicates the correct meaning in Wikidata where data and values are annotated with each label. It is a very difficult task for a machine to correctly understand or infer its meaning. For this to happen, data must be accurately tagged. Wikidata has a label for each document. In addition, it has the characteristic of being linked to another document through these documents. These connected data can be represented as graphs. In this paper, a method is proposed to create a graph based on related elements and infer the relationship of other elements using advanced Wikidata SPARQL queries. Above all, this approach helps in interpreting clear inference relationships and provides a very suitable approach in an environment where data changes frequently such as an open access database.