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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 71–80 of 151 papers

Title	Date	Tasks	Status	Hype	Score
Relation Extraction with Contextualized Relation Embedding (CRE)	Nov 19, 2020	Entity EmbeddingsRelation	CodeCode Available	0	5
SeDyT: A General Framework for Multi-Step Event Forecasting via Sequence Modeling on Dynamic Entity Embeddings	Sep 9, 2021	Entity EmbeddingsGraph Neural Network	CodeCode Available	0	5
SocialVec: Social Entity Embeddings	Nov 5, 2021	Entity EmbeddingsWord Embeddings	CodeCode Available	0	5
TempCaps: A Capsule Network-based Embedding Model for Temporal Knowledge Graph Completion	May 1, 2022	Entity EmbeddingsKnowledge Graph Completion	CodeCode Available	0	5
Unlocking the Power of Large Language Models for Entity Alignment	Feb 23, 2024	Code TranslationEntity Alignment	CodeCode Available	0	5
Word Embeddings for Entity-annotated Texts	Feb 6, 2019	ClusteringEntity Embeddings	CodeCode Available	0	5
Apprendre des repr\'esentations jointes de mots et d'entit\'es pour la d\'esambigu\" d'entit\'es (Combining Word and Entity Embeddings for Entity Linking)	Jun 1, 2017	Entity EmbeddingsEntity Linking	—Unverified	0	0
A Neural Pipeline Approach for the PharmaCoNER Shared Task using Contextual Exhaustive Models	Nov 1, 2019	Entity Embeddingsnamed-entity-recognition	—Unverified	0	0
Supervised Typing of Big Graphs using Semantic Embeddings	Mar 22, 2017	Entity EmbeddingsFeature Engineering	—Unverified	0	0
DisenE: Disentangling Knowledge Graph Embeddings	Oct 28, 2020	Entity EmbeddingsGraph Embedding	—Unverified	0	0

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