Knowledge Graph Embeddings: Open Challenges and Opportunities

Knowledge Graph Embeddings: Open Challenges and Opportunities

While Knowledge Graphs (KGs) have long been used as valuable sources of structured knowledge, in recent years, KG embeddings have become a popular way of deriving numeric vector representations from them, for instance, to support knowledge graph completion and similarity search. This study surveys a...

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Bibliographic Details
Main Authors: Biswas, Russa, Kaffee, Lucie-Aimée, Cochez, Michael, Dumbrava, Stefania, Jendal, Theis E., Lissandrini, Matteo, Lopez, Vanessa, Mencía, Eneldo Loza, Paulheim, Heiko, Sack, Harald, Vakaj, Edlira Kalemi, de Melo, Gerard
Format: Article
Language:English
Published: Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik 2023-12-01
Series:Transactions on Graph Data and Knowledge
Subjects:
knowledge graphs
kg embeddings
link prediction
kg applications
Online Access:https://drops.dagstuhl.de/storage/08tgdk/tgdk-vol001/tgdk-vol001-issue001/TGDK.1.1.4/TGDK.1.1.4.pdf

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https://drops.dagstuhl.de/storage/08tgdk/tgdk-vol001/tgdk-vol001-issue001/TGDK.1.1.4/TGDK.1.1.4.pdf

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