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Entity Embeddings

13 papers with code · Methodology

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Entity Embeddings of Categorical Variables

22 Apr 2016entron/entity-embedding-rossmann

As entity embedding defines a distance measure for categorical variables it can be used for visualizing categorical data and for data clustering.

ENTITY EMBEDDINGS

DeepType: Multilingual Entity Linking by Neural Type System Evolution

3 Feb 2018openai/deeptype

The wealth of structured (e. g. Wikidata) and unstructured data about the world available today presents an incredible opportunity for tomorrow's Artificial Intelligence.

ENTITY EMBEDDINGS ENTITY LINKING STOCHASTIC OPTIMIZATION

End-to-End Neural Entity Linking

CONLL 2018 dalab/end2end_neural_el

Entity Linking (EL) is an essential task for semantic text understanding and information extraction.

ENTITY DISAMBIGUATION ENTITY EMBEDDINGS ENTITY LINKING

Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs

ICML 2017 INK-USC/RENet

The occurrence of a fact (edge) is modeled as a multivariate point process whose intensity function is modulated by the score for that fact computed based on the learned entity embeddings.

ENTITY EMBEDDINGS KNOWLEDGE GRAPHS RELATIONAL REASONING

Jointly Learning Entity and Relation Representations for Entity Alignment

20 Sep 2019THU-KEG/Entity_Alignment_Papers

Entity alignment is a viable means for integrating heterogeneous knowledge among different knowledge graphs (KGs).

ENTITY ALIGNMENT ENTITY EMBEDDINGS KNOWLEDGE GRAPHS

Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network

ACL 2019 THU-KEG/Entity_Alignment_Papers

Previous cross-lingual knowledge graph (KG) alignment studies rely on entity embeddings derived only from monolingual KG structural information, which may fail at matching entities that have different facts in two KGs.

ENTITY EMBEDDINGS GRAPH MATCHING

Multi-relational Poincaré Graph Embeddings

23 May 2019ibalazevic/multirelational-poincare

Hyperbolic embeddings have recently gained attention in machine learning due to their ability to represent hierarchical data more accurately and succinctly than their Euclidean analogues.

ENTITY EMBEDDINGS KNOWLEDGE GRAPHS LINK PREDICTION

Incorporating Literals into Knowledge Graph Embeddings

3 Feb 2018SmartDataAnalytics/LiteralE

Most of the existing work on embedding (or latent feature) based knowledge graph analysis focuses mainly on the relations between entities.

ENTITY EMBEDDINGS KNOWLEDGE GRAPH EMBEDDINGS KNOWLEDGE GRAPHS LINK PREDICTION

Word Embeddings for Entity-annotated Texts

6 Feb 2019satya77/Entity_Embedding

We discuss two distinct approaches to the generation of such embeddings, namely the training of state-of-the-art embeddings on raw text and annotated versions of the corpus, as well as node embeddings of a co-occurrence graph representation of the annotated corpus.

ENTITY EMBEDDINGS INFORMATION RETRIEVAL WORD EMBEDDINGS