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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 126–150 of 156 papers

TitleStatusHype
An Interpretable Knowledge Transfer Model for Knowledge Base Completion—0
Improving Neural Knowledge Base Completion with Cross-Lingual Projections—0
A survey of embedding models of entities and relationships for knowledge graph completionCode0
Modeling Relational Data with Graph Convolutional NetworksCode1
Compositional Learning of Relation Path Embedding for Knowledge Base Completion—0
Link Prediction using Embedded Knowledge Graphs—0
Mining Inference Formulas by Goal-Directed Random Walks—0
Improved Knowledge Base Completion by Path-Augmented TransR Model—0
Knowledge Base Completion via Coupled Path Ranking—0
Commonsense Knowledge Base Completion—0
Incorporating Relational Knowledge into Word Representations using Subspace Regularization—0
STransE: a novel embedding model of entities and relationships in knowledge basesCode0
Corpus-level Fine-grained Entity Typing Using Contextual Information—0
Neighborhood Mixture Model for Knowledge Base Completion—0
Incorporating Selectional Preferences in Multi-hop Relation Extraction—0
Knowledge-Guided Linguistic Rewrites for Inference Rule VerificationCode0
A Factorization Machine Framework for Testing Bigram Embeddings in Knowledgebase Completion—0
Representing Text for Joint Embedding of Text and Knowledge Bases—0
Efficient and Expressive Knowledge Base Completion Using Subgraph Feature Extraction—0
Observed versus latent features for knowledge base and text inference—0
Traversing Knowledge Graphs in Vector SpaceCode0
Combining Two And Three-Way Embeddings Models for Link Prediction in Knowledge BasesCode0
Towards Combined Matrix and Tensor Factorization for Universal Schema Relation Extraction—0
Modeling Relation Paths for Representation Learning of Knowledge BasesCode0
Probabilistic Belief Embedding for Knowledge Base Completion—0
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