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Harald Sack

As a 2nd topic of this last lecture, we were discussing Completion. Most simple approach for unsupervised based on (here translation-based) knowledge graph embeddings was explained on the example of Isaac Asimov.
Slides: drive.google.com/file/d/1atNvM
@fizise @enorouzi

Slide from the last Information Service Engineering 2023 lecture, ISE Applications, 5.2 Knowledge Graph Completion: Link Prediction with KG Embeddings - Use Translational Embeddings -- Unsupervised methods, e.g. TransE, use zs + zp to predict zo -- Supervised Methods for prediction, based on embedding vectors Vectors for "Isaac Asimov" and "occupation" are added. For the resulting vector a nearest neighbor search is conducted to find - besides others - "SciFi Writer".
Jul 28, 2023, 10:22 AM·Public·Web
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