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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 51–60 of 151 papers

Title	Date	Tasks	Status	Hype	Score
DyVo: Dynamic Vocabularies for Learned Sparse Retrieval with Entities	Oct 10, 2024	Document RankingEntity Embeddings	CodeCode Available	0	5
An entity-guided text summarization framework with relational heterogeneous graph neural network	Feb 7, 2023	Entity EmbeddingsGraph Neural Network	CodeCode Available	0	5
Conflict-Aware Pseudo Labeling via Optimal Transport for Entity Alignment	Sep 5, 2022	Entity AlignmentEntity Embeddings	CodeCode Available	0	5
Entity Embeddings of Categorical Variables	Apr 22, 2016	ClusteringEntity Embeddings	CodeCode Available	0	5
Inductive Link Prediction in Knowledge Graphs using Path-based Neural Networks	Dec 16, 2023	Entity EmbeddingsInductive Link Prediction	CodeCode Available	0	5
Inductive Logical Query Answering in Knowledge Graphs	Oct 13, 2022	Complex Query AnsweringEntity Embeddings	CodeCode Available	0	5
Entity or Relation Embeddings? An Analysis of Encoding Strategies for Relation Extraction	Dec 18, 2023	Entity EmbeddingsLanguage Modeling	CodeCode Available	0	5
Ered: Enhanced Text Representations with Entities and Descriptions	Aug 18, 2022	Entity Embeddings	CodeCode Available	0	5
Informed Multi-context Entity Alignment	Jan 2, 2022	Entity AlignmentEntity Embeddings	CodeCode Available	0	5
KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation	Nov 13, 2019	Entity EmbeddingsEntity Typing	CodeCode Available	0	5

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