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Nandini, Durgesh ; Blöthner, Simon ; Schönfeld, Mirco ; Larch, Mario:
Multidimensional Knowledge Graph Embeddings for International Trade Flow Analysis.
2024
Veranstaltung: 16th International Conference on Knowledge Engineering and Ontology Development
, 17.-19. November 2024
, Porto, Portugal.
(Veranstaltungsbeitrag: Kongress/Konferenz/Symposium/Tagung
,
Paper
)
DOI: https://doi.org/10.5220/0013028500003838
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| Projekttitel: |
Offizieller Projekttitel Projekt-ID Consideration of Contextual Factors and Structural Conditions in a Dynamic Framework (KONECO) 16DKWN095 |
|---|---|
| Projektfinanzierung: |
Bundesministerium für Bildung und Forschung |
Abstract
Understanding the complex dynamics of high-dimensional, contingent, and strongly nonlinear economic data, often shaped by multiplicative processes, poses significant challenges for traditional regression methods as such methods offer limited capacity to capture the structural changes they feature. To address this, we propose leveraging the potential of knowledge graph embeddings for economic trade data, in particular, to predict international trade relationships. We implement KonecoKG, a knowledge graph representation of economic trade data with multidimensional relationships using SDM-RDFizer and transform the relationships into a knowledge graph embedding using AmpliGraph.