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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 111–120 of 156 papers

TitleStatusHype
Revisiting Simple Neural Networks for Learning Representations of Knowledge GraphsCode0
KBGAN: Adversarial Learning for Knowledge Graph EmbeddingsCode0
Weakly-supervised Relation Extraction by Pattern-enhanced Embedding Learning—0
Fast Linear Model for Knowledge Graph EmbeddingsCode0
Why PairDiff works? -- A Mathematical Analysis of Bilinear Relational Compositional Operators for Analogy Detection—0
KBLRN : End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical FeaturesCode0
Compositional Approaches for Representing Relations Between Words: A Comparative Study—0
Corpus-level Fine-grained Entity Typing—0
Modeling Large-Scale Structured Relationships with Shared Memory for Knowledge Base Completion—0
NTNU-2 at SemEval-2017 Task 10: Identifying Synonym and Hyponym Relations among Keyphrases in Scientific Documents—0
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