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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 121–130 of 156 papers

TitleStatusHype
Semantically Enhanced Models for Commonsense Knowledge Acquisition—0
Data-dependent Learning of Symmetric/Antisymmetric Relations for Knowledge Base Completion—0
Neural Markov Logic Networks—0
Distributed Prediction of Relations for Entities: The Easy, The Difficult, and The Impossible—0
Distributional Negative Sampling for Knowledge Base Completion—0
DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections—0
Neural Relation Extraction via Inner-Sentence Noise Reduction and Transfer Learning—0
NTNU-2 at SemEval-2017 Task 10: Identifying Synonym and Hyponym Relations among Keyphrases in Scientific Documents—0
Observed versus latent features for knowledge base and text inference—0
Efficient and Expressive Knowledge Base Completion Using Subgraph Feature Extraction—0
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