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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 21–30 of 151 papers

Title	Date	Tasks	Status	Hype
Improving Entity Linking through Semantic Reinforced Entity Embeddings	Jun 16, 2021	ArticlesEntity Embeddings	CodeCode Available	1
Highly Efficient Knowledge Graph Embedding Learning with Orthogonal Procrustes Analysis	Apr 10, 2021	Entity EmbeddingsGraph Embedding	CodeCode Available	1
CoLAKE: Contextualized Language and Knowledge Embedding	Oct 1, 2020	Entity EmbeddingsKnowledge Graph Completion	CodeCode Available	1
Inductive Learning on Commonsense Knowledge Graph Completion	Sep 19, 2020	DecoderEntity Embeddings	CodeCode Available	1
TransEdge: Translating Relation-contextualized Embeddings for Knowledge Graphs	Apr 22, 2020	Entity AlignmentEntity Embeddings	CodeCode Available	1
Contextual Parameter Generation for Knowledge Graph Link Prediction	Apr 3, 2020	Entity EmbeddingsLink Prediction	CodeCode Available	1
Message Passing Query Embedding	Feb 6, 2020	Entity EmbeddingsGraph Neural Network	CodeCode Available	1
MRAEA: An Efficient and Robust Entity Alignment Approach for Cross-lingual Knowledge Graph	Feb 3, 2020	Entity AlignmentEntity Embeddings	CodeCode Available	1
Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs	Aug 22, 2019	Entity AlignmentEntity Embeddings	CodeCode Available	1
RDF2Vec: RDF Graph Embeddings and Their Applications	Nov 10, 2017	Entity EmbeddingsGeneral Knowledge	CodeCode Available	1

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