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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 76–100 of 156 papers

TitleStatusHype
Probabilistic Belief Embedding for Knowledge Base Completion—0
Projected Canonical Decomposition for Knowledge Base Completion—0
Query-Driven Knowledge Base Completion using Multimodal Path Fusion over Multimodal Knowledge Graph—0
Reasoning Over Paths via Knowledge Base Completion—0
Reasoning With Neural Tensor Networks for Knowledge Base Completion—0
Recurrent One-Hop Predictions for Reasoning over Knowledge Graphs—0
Relation Induction in Word Embeddings Revisited—0
Representing Text for Joint Embedding of Text and Knowledge Bases—0
Revisiting Evaluation of Knowledge Base Completion Models—0
Revisiting the Task of Scoring Open IE Relations—0
Riemannian TransE: Multi-relational Graph Embedding in Non-Euclidean Space—0
Semantically Enhanced Models for Commonsense Knowledge Acquisition—0
Text-Based Joint Prediction of Numeric and Categorical Attributes of Entities in Knowledge Bases—0
Towards a Continuous Knowledge Learning Engine for Chatbots—0
Towards Combined Matrix and Tensor Factorization for Universal Schema Relation Extraction—0
Weakly-supervised Relation Extraction by Pattern-enhanced Embedding Learning—0
Why a Naive Way to Combine Symbolic and Latent Knowledge Base Completion Works Surprisingly Well—0
Why does PairDiff work? - A Mathematical Analysis of Bilinear Relational Compositional Operators for Analogy Detection—0
Why PairDiff works? -- A Mathematical Analysis of Bilinear Relational Compositional Operators for Analogy Detection—0
Efficient and Expressive Knowledge Base Completion Using Subgraph Feature Extraction—0
Efficient Parallel Multi-Hop Reasoning: A Scalable Approach for Knowledge Graph Analysis—0
Embedding Cardinality Constraints in Neural Link Predictors—0
Evaluating the Knowledge Base Completion Potential of GPT—0
Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning—0
Extracting triples from dialogues for conversational social agents—0
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