Abstract
Knowledge graphs are being used for the detection of money laundering, insurance fraud, and other suspicious activities. Some recent work demonstrated how knowledge graphs are being used to study the impact of the COVID-19 outbreak on the economy. The fact that knowledge graphs are being used in more and more interdisciplinary problems calls for a reliable source of interdisciplinary knowledge. In this paper, we study the integration of knowledge graphs in the domains of economics, banking, and finance. Our integrated knowledge graph has over 610K nodes and 1.7 million edges. By performing statistical and graph-theoretical analysis, we demonstrate how the integration results in more entities with richer information. Its quality was examined by analyzing the subgraphs of the identity links and (pseudo-)transitive relations. Finally, we study the sources of error, and their refinement and discuss the benefit of our integrated graph.
| Original language | English |
|---|---|
| Title of host publication | EDBT/ICDT-WS 2022 EDBT/ICDT 2022 Workshops |
| Subtitle of host publication | Proceedings of the Workshops of the EDBT/ICDT 2022 Joint Conference Edinburgh, UK, March 29, 2022 |
| Publisher | CEUR-WS.org |
| Pages | 1-6 |
| Number of pages | 6 |
| Publication status | Published - 16 May 2022 |
| Externally published | Yes |
| Event | 2022 Workshops of the EDBT/ICDT Joint Conference, EDBT/ICDT-WS 2022 - , United Kingdom Duration: 29 Mar 2022 → … |
Conference
| Conference | 2022 Workshops of the EDBT/ICDT Joint Conference, EDBT/ICDT-WS 2022 |
|---|---|
| Country/Territory | United Kingdom |
| Period | 29/03/22 → … |
Keywords
- Integrated knowledge graphs
- knowledge graph analysis
- knowledge graph refinement
- SDG 17 - Partnerships for the Goals
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