Generating conceptual subgraph from tabular data for knowledge graph matching

Donguk Kim, Heesung Park, Jae Kyu Lee, Wooju Kim

Research output: Contribution to journalConference articlepeer-review

3 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)96-103
Number of pages8
JournalCEUR Workshop Proceedings
Publication statusPublished - 2020
Event2020 Semantic Web Challenge on Tabular Data to Knowledge Graph Matching, SemTab 2020 - Virtual, Online
Duration: 2020 Nov 5 → …

Bibliographical note

Publisher Copyright:
Copyright © 2020 for this paper by its authors.

All Science Journal Classification (ASJC) codes

  • General Computer Science


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