Entity Embeddings

50 papers with code • 0 benchmarks • 2 datasets

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Most implemented papers

Entity Embeddings of Categorical Variables

entron/entity-embedding-rossmann 22 Apr 2016

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

A Deep Learning System for Predicting Size and Fit in Fashion E-Commerce

NeverInAsh/fit-recommendation 23 Jul 2019

To alleviate this problem, we propose a deep learning based content-collaborative methodology for personalized size and fit recommendation.

Scalable Zero-shot Entity Linking with Dense Entity Retrieval

facebookresearch/BLINK EMNLP 2020

This paper introduces a conceptually simple, scalable, and highly effective BERT-based entity linking model, along with an extensive evaluation of its accuracy-speed trade-off.

Know-Evolve: Deep Temporal Reasoning for Dynamic Knowledge Graphs

rstriv/Know-Evolve ICML 2017

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.

Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network

syxu828/Crosslingula-KG-Matching ACL 2019

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.

DAWT: Densely Annotated Wikipedia Texts across multiple languages

klout/opendata 2 Mar 2017

In addition to the main dataset, we open up several derived datasets including mention entity co-occurrence counts and entity embeddings, as well as mappings between Freebase ids and Wikidata item ids.

Named Entity Disambiguation for Noisy Text

yotam-happy/NEDforNoisyText CONLL 2017

We address the task of Named Entity Disambiguation (NED) for noisy text.

RDF2Vec: RDF Graph Embeddings and Their Applications

IBCNServices/pyRDF2Vec Semantic Web Journal 2017

Linked Open Data has been recognized as a valuable source for background information in many data mining and information retrieval tasks.

Incorporating Literals into Knowledge Graph Embeddings

SmartDataAnalytics/LiteralE 3 Feb 2018

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

DeepType: Multilingual Entity Linking by Neural Type System Evolution

openai/deeptype 3 Feb 2018

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