Multidimensional Knowledge Graph Embeddings for International Trade Flow Analysis

• URL: http://arxiv.org/abs/2410.19835v1
• Date: Sat, 19 Oct 2024 20:28:20 GMT
• Title: Multidimensional Knowledge Graph Embeddings for International Trade Flow Analysis
• Authors: Durgesh Nandini, Simon Bloethner, Mirco Schoenfeld, Mario Larch,
• Abstract summary: We propose leveraging the potential of knowledge graph embeddings for economic trade data 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.
• Score: 0.2688651203805043
• License:
• 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.

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