Knowledge Graph Embeddings

108 papers with code • 0 benchmarks • 4 datasets

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Use these libraries to find Knowledge Graph Embeddings models and implementations
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Most implemented papers

Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction

MIRALab-USTC/KGE-HAKE 21 Nov 2019

HAKE is inspired by the fact that concentric circles in the polar coordinate system can naturally reflect the hierarchy.

Convolutional 2D Knowledge Graph Embeddings

TimDettmers/ConvE 5 Jul 2017

In this work, we introduce ConvE, a multi-layer convolutional network model for link prediction, and report state-of-the-art results for several established datasets.

Multi-Relational Embedding for Knowledge Graph Representation and Analysis

tranhungnghiep/AnalyzeKGE PhD Dissertation, The Graduate University for Advanced Studies, SOKENDAI, Japan 2020

The goal of this thesis is first to study multi-relational embedding on knowledge graphs to propose a new embedding model that explains and improves previous methods, then to study the applications of multi-relational embedding in representation and analysis of knowledge graphs.

KBGAN: Adversarial Learning for Knowledge Graph Embeddings

cai-lw/KBGAN NAACL 2018

This framework is independent of the concrete form of generator and discriminator, and therefore can utilize a wide variety of knowledge graph embedding models as its building blocks.

Seq2RDF: An end-to-end application for deriving Triples from Natural Language Text

YueLiu/NeuralTripleTranslation 4 Jul 2018

Inspired by recent successes in neural machine translation, we treat the triples within a given knowledge graph as an independent graph language and propose an encoder-decoder framework with an attention mechanism that leverages knowledge graph embeddings.

Multi-Hop Knowledge Graph Reasoning with Reward Shaping

salesforce/MultiHopKG EMNLP 2018

Multi-hop reasoning is an effective approach for query answering (QA) over incomplete knowledge graphs (KGs).

Low-Dimensional Hyperbolic Knowledge Graph Embeddings

tensorflow/neural-structured-learning ACL 2020

However, existing hyperbolic embedding methods do not account for the rich logical patterns in KGs.

Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings

NIVA-Knowledge-Graph/TERA 8 Dec 2021

Furthermore, we have implemented a fine-tuning architecture that adapts the knowledge graph embeddings to the effect prediction task and leads to better performance.

Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment

muhaochen/MTransE 12 Nov 2016

Many recent works have demonstrated the benefits of knowledge graph embeddings in completing monolingual knowledge graphs.