# TransEdge: Translating Relation-contextualized Embeddings for Knowledge Graphs

arXiv: https://arxiv.org/abs/2004.13579 · HTML: https://mlsanity.com/paper/2004.13579/

## Key facts

- Cited by 41 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Apr 2020.

## Built on by (most cited first, 30 of 41)

- [Boosting the Speed of Entity Alignment 10*: Dual Attention Matching Network with Normalized Hard Sample Mining](https://mlsanity.com/paper/2103.15452/) (2021)
- [SelfKG: Self-Supervised Entity Alignment in Knowledge Graphs](https://mlsanity.com/paper/2203.01044/) (2022)
- [A Benchmark and Comprehensive Survey on Knowledge Graph Entity Alignment via Representation Learning](https://mlsanity.com/paper/2103.15059/) (2021)
- [MEAformer: Multi-modal Entity Alignment Transformer for Meta Modality Hybrid](https://mlsanity.com/paper/2212.14454/) (2022)
- [RAGA: Relation-aware Graph Attention Networks for Global Entity Alignment](https://mlsanity.com/paper/2103.00791/) (2021)
- [Rethinking Uncertainly Missing and Ambiguous Visual Modality in Multi-Modal Entity Alignment](https://mlsanity.com/paper/2307.16210/) (2023)
- [Knowing the No-match: Entity Alignment with Dangling Cases](https://mlsanity.com/paper/2106.02248/) (2021)
- [ClusterEA: Scalable Entity Alignment with Stochastic Training and Normalized Mini-batch Similarities](https://mlsanity.com/paper/2205.10312/) (2022)
- [LightEA: A Scalable, Robust, and Interpretable Entity Alignment Framework via Three-view Label Propagation](https://mlsanity.com/paper/2210.10436/) (2022)
- [MKGL: Mastery of a Three-Word Language](https://mlsanity.com/paper/2410.07526/) (2024)
- [Improving Conversational Recommendation System by Pretraining on Billions Scale of Knowledge Graph](https://mlsanity.com/paper/2104.14899/) (2021)
- [Are Negative Samples Necessary in Entity Alignment? An Approach with High Performance, Scalability and Robustness](https://mlsanity.com/paper/2108.05278/) (2021)
- [Facing Changes: Continual Entity Alignment for Growing Knowledge Graphs](https://mlsanity.com/paper/2207.11436/) (2022)
- [Two Heads Are Better Than One: Integrating Knowledge from Knowledge Graphs and Large Language Models for Entity Alignment](https://mlsanity.com/paper/2401.16960/) (2024)
- [Reinforcement Learning based Collective Entity Alignment with Adaptive Features](https://mlsanity.com/paper/2101.01353/) (2021)
- [AutoAlign: Fully Automatic and Effective Knowledge Graph Alignment enabled by Large Language Models](https://mlsanity.com/paper/2307.11772/) (2023)
- [From Alignment to Entailment: A Unified Textual Entailment Framework for Entity Alignment](https://mlsanity.com/paper/2305.11501/) (2023)
- [Towards Entity Alignment in the Open World: An Unsupervised Approach](https://mlsanity.com/paper/2101.10535/) (2021)
- [μKG: A Library for Multi-source Knowledge Graph Embeddings and Applications](https://mlsanity.com/paper/2207.11442/) (2022)
- [What Makes Entities Similar? A Similarity Flooding Perspective for Multi-sourced Knowledge Graph Embeddings](https://mlsanity.com/paper/2306.02622/) (2023)
- [Lambda: Learning Matchable Prior For Entity Alignment with Unlabeled Dangling Cases](https://mlsanity.com/paper/2403.10978/) (2024)
- [IBMEA: Exploring Variational Information Bottleneck for Multi-modal Entity Alignment](https://mlsanity.com/paper/2407.19302/) (2024)
- [A Self-supervised Method for Entity Alignment](https://mlsanity.com/paper/2106.09395/) (2021)
- [EchoEA: Echo Information between Entities and Relations for Entity Alignment](https://mlsanity.com/paper/2107.03054/) (2021)
- [Combating Confirmation Bias: A Unified Pseudo-Labeling Framework for Entity Alignment](https://mlsanity.com/paper/2307.02075/) (2023)
- [i-Align: an interpretable knowledge graph alignment model](https://mlsanity.com/paper/2308.13755/) (2023)
- [Universal Multi-modal Entity Alignment via Iteratively Fusing Modality Similarity Paths](https://mlsanity.com/paper/2310.05364/) (2023)
- [Gradient Flow of Energy: A General and Efficient Approach for Entity Alignment Decoding](https://mlsanity.com/paper/2401.12798/) (2024)
- [LoginMEA: Local-to-Global Interaction Network for Multi-modal Entity Alignment](https://mlsanity.com/paper/2407.19625/) (2024)
- [Aligning Multiple Knowledge Graphs in a Single Pass](https://mlsanity.com/paper/2408.00662/) (2024)

## Abstract (arXiv)

Learning knowledge graph (KG) embeddings has received increasing attention in recent years. Most embedding models in literature interpret relations as linear or bilinear mapping functions to operate on entity embeddings. However, we find that such relation-level modeling cannot capture the diverse relational structures of KGs well. In this paper, we propose a novel edge-centric embedding model TransEdge, which contextualizes relation representations in terms of specific head-tail entity pairs. We refer to such contextualized representations of a relation as edge embeddings and interpret them as translations between entity embeddings. TransEdge achieves promising performance on different prediction tasks. Our experiments on benchmark datasets indicate that it obtains the state-of-the-art results on embedding-based entity alignment. We also show that TransEdge is complementary with conventional entity alignment methods. Moreover, it shows very competitive performance on link prediction.