KGE

Some papers on Knowledge Graph Embedding (KGE).

I am terribly sorry that the original repository is blocked.

Thanks for your attention and kind words! I will update KGE later.

Contents

• Survey
• Methods
• Papers

Survey

Methods

Papers

2026

Journal

• <a name="GIRMSF"></a> (GIRMSF) Lin Lin, Shiwei Suo, Song Fu, Lizheng Zu, Sihao Zhang, Yikun Liu. "GIRMSF-global information reconstruction and multi-scale feature sharpening framework for knowledge graph embedding". Expert Systems with Applications 2026. paper

• <a name="SuKE"></a> (SuKE) Yunhai Ye, Shuo Wang. "SuKE: Structural Knowledge Extractor enhances large language model for knowledge graph completion". Expert Systems with Applications 2026. paper

• <a name="RSPED"></a> (RSPED) Rushan Geng, Cuicui Luo. "Exploring relevant snapshots and neighboring entities for temporal knowledge graph reasoning". Information Processing and Management 2026. paper

• <a name="ReHGD"></a> (ReHGD) Jibing Gong, Yuting Lin, Yi Zhao, Tianyu Lin, Xiaohan Fang, Xinchao Feng, Jiquan Peng. "Reinforced Heterogeneous Graphlet Design for Knowledge Graph Representation Learning". Information Sciences 2026. paper

2025

Journal

• <a name="RGAT-PRotatE"></a> (RGAT-PRotatE) Chang Su, Qi Jiang, Yong Han, Tao Wang, Qingchen He. "Knowledge graph-driven decision support for manufacturing process: A graph neural network-based knowledge reasoning approachm". Advanced Engineering Informatics 2025. paper

• <a name="BHRAM"></a> (BHRAM) Chaoqun Zhang, Wanqiu Li, Yuanbin Mo, Weidong Tang, Haoran Li, Zhilin Zeng. "BHRAM: a knowledge graph embedding model based on bidirectional and heterogeneous relational attention mechanism". Applied Intelligence 2025. paper

• <a name="CALP"></a> (CALP) Shijie Zan, Weidong Ji, Guohui Zhou. "Knowledge graph embeddings based on 2d convolution and self-attention mechanisms for link prediction". Applied Intelligence 2025. paper

• <a name="DA-ARKGC"></a> (DA-ARKGC) Na Zhou, Yuan Yuan, Lei Chen. "A two-stage knowledge graph completion based on LLMs' data augmentation and atrous spatial pyramid pooling". Applied Intelligence 2025. paper

• <a name="DARKR"></a> (DARKR) Xuhua Yang, Tao Wang, Ji-Song Gan, Liang-Yu Gao, Gang-Feng Ma, Yan-Bo Zhou. "Reinforcement knowledge graph reasoning based on dual agents and attention mechanism". Applied Intelligence 2025. paper

• Hao Liu, Dong Li, Bing Zeng, Yang Xu. "Learning discriminative features for multi-hop knowledge graph reasoning". Applied Intelligence 2025. paper

• <a name="EDMSConvKE"></a> (EDMSConvKE) Panfei Yin, Erping Zhao, Bianbadroma, Ngodrup. "A knowledge graph completion model based on weighted fusion description information and transform of the dimension and the scale". Applied Intelligence 2025. paper

• <a name="ERAGNN"></a> (ERAGNN) Guoshun Xu, Guozheng Rao, Li Zhang, Qing Cong. "Entity-relation aggregation mechanism graph neural network for knowledge graph embedding". Applied Intelligence 2025. paper

• <a name="GLARGCN"></a> (GLARGCN) Shuo Wang, Shuxu Chen, Zhaoqian Zhong. "Global and local information-aware relational graph convolutional network for temporal knowledge graph completion". Applied Intelligence 2025. paper

• <a name="LTRGN"></a> (LTRGN) Weida Liu, Baohua Qiang, Ruidong Chen, Yuan Xie, Lirui Chen, Zhiqin Chen. "Linear self-attention with multi-relational graph for knowledge graph completion". Applied Intelligence 2025. paper

• <a name="MPLR"></a> (MPLR) Haotian Li, Bailing Wang, Kai Wang, Rui Zhang, Yuliang Wei. "An original model for multi-target learning of logical rules for knowledge graph reasoning". Applied Intelligence 2025. paper

• <a name="MSDE"></a> (MSDE) Tianyi Xu, Yan Wang, Wenbin Zhang, Yue Zhao, Jian Yu, Mei Yu, Jiujiang Guo, Mankun Zhao. "Multi-perspective semantic decoupling and enhancement in graph attention network for knowledge graph completion". Applied Intelligence 2025. paper

• <a name="NP-FedKGC"></a> (NP-FedKGC) Songsong Liu, Wenxin Li, Xiao Song, Kaiqi Gong. "NP-FedKGC: a neighbor prediction-enhanced federated knowledge graph completion model". Applied Intelligence 2025. paper

• <a name="OTMKGRL"></a> (OTMKGRL) Tao Wang, Bo Shen. "OTMKGRL:a universal multimodal knowledge graph representation learning framework using optimal transport and cross-modal relation". Applied Intelligence 2025. paper

• <a name="PFedEG"></a> (PFedEG) Xiaoxiong Zhang, Zhiwei Zeng, Xin Zhou, Dusit Niyato, Zhiqi Shen. "Personalized federated knowledge graph embedding with client-wise relation graph". Applied Intelligence 2025. paper

• <a name="REFD"></a> (REFD) Qian Liu, Siling Feng, Mengxing Huang, Uzair Aslam Bhatti. "REFD:recurrent encoder and fusion decoder for temporal knowledge graph reasoning". Applied Intelligence 2025. paper

• <a name="SFP"></a> (SFP) Jingbin Wang, Xifan Ke, Fufuan Zhang, Yuwei Wu, Sirui Zhang, Kun Guo. "SFP: temporal knowledge graph completion based on sequence-focus patterns representation learning". Applied Intelligence 2025. paper

• Linlan Liu, Weide Huang, Jian Shu, Hongjian Zhao. "Knowledge graph relation prediction based on graph transformation". Applied Intelligence 2025. paper

• Hao Liu, Dong Li, Bing Zeng, Yang Xu. "Learning discriminative features for multi-hop knowledge graph reasoning". Applied Intelligence 2025. paper

• <a name="MANNER"></a> (MANNER) Shensi Wang, Kun Fu, Xian Sun, Zequn Zhang, Li Jin, Yuying Shang, Shiyao Yan. "How to learn new knowledge: a multimodal contrastive learning framework for open-world knowledge graph completion". Applied Intelligence 2025. paper

• <a name="MRCCA"></a> (MRCCA) Sifan Cao, Xiaodong Li, Zhaozhe Gong, Fengjun Xiao, Jing Chen, Zhengsheng Yu. "Multiple concepts and cross-attention based knowledge graph completion". Applied Intelligence 2025. paper

• <a name="SimRMKGC"></a> (SimRMKGC) Xiaohan Fang, Qian Zang, Jibing Gong, Tao Fang, Yili Xu, Xi Wu:. "SimRMKGC: Simple relational contrastive learning on multilingual knowledge graph completion". Applied Intelligence 2025. paper

• <a name="CoAE-GCN"></a> (CoAE-GCN) Dong Zhang, Wenhao Li, Tianbo Qiu, Guanyu Li. "Co-occurrence Graph Convolutional Networks with Approximate Entailment for knowledge graph embedding". Applied Soft Computing 2025. paper

• <a name="DMGNN"></a> (DMGNN) Bingbing Dong, Chenyang Bu, Ye Wang, Yi Zhu, Xindong Wu. "Disentangled Multi-view Graph Neural Network for multilingual knowledge graph completion". Applied Soft Computing 2025. paper

• <a name="JointDE"></a> (JointDE) Mingsheng He, Lin Zhu, Luyi Bai. "Jointly leveraging 1D and 2D convolution on diachronic entity embedding for temporal knowledge graph completion". Applied Soft Computing 2025. paper

• <a name="KGCD"></a> (KGCD) Wenlong Hou, Weidong Zhao, Ning Jia, Xianhui Liu. "Low-resource knowledge graph completion based on knowledge distillation driven by large language models". Applied Soft Computing 2025. paper

• <a name="RP-KGC"></a> (RP-KGC) Wenying Guo, Shengdong Du, Jie Hu, Fei Teng, Yan Yang, Tianrui Li. "RP-KGC: A Knowledge Graph Completion Model Integrating Rule-Based Knowledge for Pretraining and Inference". Big Data Mining and Analytics 2025. paper

• <a name="TRenD"></a> (TRenD) Ye Wang, Binxing Fang, Shuxian Huang, Kai Chen, Yan Jia, Aiping Li. "Extrapolation Reasoning on Temporal Knowledge Graphs via Temporal Dependencies Learning". **`CAAI Transact