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Entity Embeddings

Entity Embeddings is a technique for applying deep learning to tabular data. It involves representing the categorical data of an information systems entity with multiple dimensions.

Papers

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Showing 91–100 of 151 papers

TitleStatusHype
A Mixture-of-Experts Model for Learning Multi-Facet Entity EmbeddingsCode0
Relation Extraction with Contextualized Relation Embedding (CRE)Code0
DisenE: Disentangling Knowledge Graph Embeddings—0
Content-Based Personalized Recommender System Using Entity Embeddings—0
Entity Embedding as Game Representation—0
CoLAKE: Contextualized Language and Knowledge EmbeddingCode1
Inductive Learning on Commonsense Knowledge Graph CompletionCode1
DensE: An Enhanced Non-commutative Representation for Knowledge Graph Embedding with Adaptive Semantic HierarchyCode0
Dual Graph Embedding for Object-Tag LinkPrediction on the Knowledge Graph—0
Neural Entity Linking: A Survey of Models Based on Deep Learning—0
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