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Knowledge Base Completion

Knowledge base completion is the task which automatically infers missing facts by reasoning about the information already present in the knowledge base. A knowledge base is a collection of relational facts, often represented in the form of "subject", "relation", "object"-triples.

Papers

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Showing 11–20 of 156 papers

TitleStatusHype
BoxE: A Box Embedding Model for Knowledge Base CompletionCode1
Canonical Tensor Decomposition for Knowledge Base CompletionCode1
K-PLUG: KNOWLEDGE-INJECTED PRE-TRAINED LANGUAGE MODEL FOR NATURAL LANGUAGE UNDERSTANDING AND GENERATIONCode1
A Factorization Machine Framework for Testing Bigram Embeddings in Knowledgebase Completion—0
Capacity and Bias of Learned Geometric Embeddings for Directed Graphs—0
Compositional Learning of Relation Path Embedding for Knowledge Base Completion—0
A Survey on Graph Neural Networks for Knowledge Graph Completion—0
Compositional Vector Space Models for Knowledge Base Completion—0
Commonsense Knowledge Base Completion and Generation—0
Combining Rules and Embeddings via Neuro-Symbolic AI for Knowledge Base Completion—0
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