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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 111–120 of 151 papers

Title	Date	Tasks	Status	Hype
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation	Nov 13, 2019	Entity EmbeddingsEntity Typing	CodeCode Available	0
Scalable Zero-shot Entity Linking with Dense Entity Retrieval	Nov 10, 2019	Entity EmbeddingsEntity Linking	CodeCode Available	2
E-BERT: Efficient-Yet-Effective Entity Embeddings for BERT	Nov 9, 2019	Entity EmbeddingsEntity Linking	CodeCode Available	0
A Neural Pipeline Approach for the PharmaCoNER Shared Task using Contextual Exhaustive Models	Nov 1, 2019	Entity Embeddingsnamed-entity-recognition	—Unverified	0
KRED: Knowledge-Aware Document Representation for News Recommendations	Oct 25, 2019	Articlesdocument understanding	CodeCode Available	0
Aligning Cross-Lingual Entities with Multi-Aspect Information	Oct 15, 2019	Entity AlignmentEntity Embeddings	CodeCode Available	0
TransGCN:Coupling Transformation Assumptions with Graph Convolutional Networks for Link Prediction	Oct 1, 2019	DecoderEntity Embeddings	—Unverified	0
Jointly Learning Entity and Relation Representations for Entity Alignment	Sep 20, 2019	Entity AlignmentEntity Embeddings	CodeCode Available	0
Relation-Aware Entity Alignment for Heterogeneous Knowledge Graphs	Aug 22, 2019	Entity AlignmentEntity Embeddings	CodeCode Available	1
A Deep Learning System for Predicting Size and Fit in Fashion E-Commerce	Jul 23, 2019	Collaborative FilteringEntity Embeddings	CodeCode Available	0

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