A class-based partitioning heuristic for parallel knowledge graph embedding training, evaluated on FB15K and FB15K-237, shows modest and model-dependent gains over random partitioning.
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A Semantic Partitioning Method for Large-Scale Training of Knowledge Graph Embeddings
A class-based partitioning heuristic for parallel knowledge graph embedding training, evaluated on FB15K and FB15K-237, shows modest and model-dependent gains over random partitioning.