KGEMs for link prediction exhibit high instability in predictions and embeddings from initialization, negative sampling, and other factors, with better MRR not ensuring higher stability.
Transactions on Graph Data and Knowledge1(1), 5:1–5:33 (2023)
2 Pith papers cite this work. Polarity classification is still indexing.
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MetaboKG supplies a transformation workflow, semantic model based on PROV-O/SIO and domain ontologies, and Universal Annotation Identifier to enable graph-based integration and SPARQL queries over 680 GNPS molecular networking results.
citing papers explorer
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Link Prediction or Perdition: the Seeds of Instability in Knowledge Graph Embeddings
KGEMs for link prediction exhibit high instability in predictions and embeddings from initialization, negative sampling, and other factors, with better MRR not ensuring higher stability.
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MetaboKG: An Analysis-centric Knowledge Graph Framework for Untargeted Metabolomics
MetaboKG supplies a transformation workflow, semantic model based on PROV-O/SIO and domain ontologies, and Universal Annotation Identifier to enable graph-based integration and SPARQL queries over 680 GNPS molecular networking results.