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Negative Sampling for Learning Knowledge Graph Embeddings
Reimplementation of four KG factorization methods and six negative sampling methods. Abstract Knowledge graphs are large, useful, but incomplete knowledge repositories. They... -
KGE Algorithms
An updated method for link prediction that uses a regularization factor that models relation argument types Abstract (Kotnis and Nastase, 2017): Learning relations based on... -
Abstract graphs, abstract paths, grounded paths for Freebase and NELL
We describe a method for representing knowledge graphs that capture an intensional representation of the original extensional information. This representation is very compact,... -
Negative Sampling for Learning Knowledge Graph Embeddings
Reimplementation of four KG factorization methods and six negative sampling methods. Abstract Knowledge graphs are large, useful, but incomplete knowledge repositories. They... -
KGE Algorithms
An updated method for link prediction that uses a regularization factor that models relation argument types Abstract (Kotnis and Nastase, 2017): Learning relations based on... -
Abstract graphs, abstract paths, grounded paths for Freebase and NELL
We describe a method for representing knowledge graphs that capture an intensional representation of the original extensional information. This representation is very compact,...
