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N-ary Knowledge Graphs (NKGs) are a specialized type of knowledge graph designed to efficiently represent complex real-world facts.
Composition-based multi-relational graph convolutional networks
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Message passing for hyper-relational knowledge graphs
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On the representation and embedding of knowledge bases beyond binary relations
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A survey on application of knowledge graph
Xiaohan Zou. 2020 · 2016
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Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017 · 2017
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Attention is all you need
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Knowledge graph embedding: A survey of approaches and applications
Quan Wang, Zhendong Mao, Bin Wang, and Li Guo. 2017 · 2017
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Wide compression: Tensor ring nets
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Scalable instance reconstruction in knowledge bases via relatedness affiliated embedding
Richong Zhang, Junpeng Li, Jiajie Mei, and Yongyi Mao. 2018 · 2018
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Meta relational learning for few-shot link prediction in knowledge graphs
Mingyang Chen, Wen Zhang, Wei Zhang, Qiang Chen, and Huajun Chen. 2019 · 2019
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Link prediction on n-ary relational data
Saiping Guan, Xiaolong Jin, Yuanzhuo Wang, and Xueqi Cheng. 2019 · 2019
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A survey on knowledge graph embedding: Approaches, applications and benchmarks
Yuanfei Dai, Shiping Wang, Neal N Xiong, and Wenzhong Guo. 2020 · 2020
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Diachronic embedding for temporal knowledge graph completion
Rishab Goel, Seyed Mehran Kazemi, Marcus Brubaker, and Pascal Poupart. 2020 · 2020
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Neuinfer: Knowledge inference on n-ary facts
Saiping Guan, Xiaolong Jin, Jiafeng Guo, Yuanzhuo Wang, and Xueqi Cheng. 2020 · 2020
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Generalizing tensor decomposition for n-ary relational knowledge bases
Yu Liu, Quanming Yao, and Yong Li. 2020 · 2020
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A survey of embedding models of entities and relationships for knowledge graph completion
Dat Quoc Nguyen. 2020 · 2020
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Beyond triplets: hyper-relational knowledge graph embedding for link prediction
Paolo Rosso, Dingqi Yang, and Philippe Cudré-Mauroux. 2020 · 2020
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Adaptive attentional network for few-shot knowledge graph completion
Jiawei Sheng, Shu Guo, Zhenyu Chen, Juwei Yue, Lihong Wang, Tingwen Liu, and Hongbo Xu. 2020 · 2020
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Few-shot knowledge graph completion
Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, and Nitesh V Chawla. 2020 · 2020
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Research on information extraction of technical documents and construction of domain knowledge graph
Huaxuan Zhao, Yueling Pan, and Feng Yang. 2020 · 2020
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Improving inductive link prediction using hyper-relational facts
Mehdi Ali, Max Berrendorf, Mikhail Galkin, Veronika Thost, Tengfei Ma, Volker Tresp, and Jens Lehmann. 2021 · 2021
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Knowledge-aware zero-shot learning: Survey and perspective
Jiaoyan Chen, Yuxia Geng, Zhuo Chen, Ian Horrocks, Jeff Z Pan, and Huajun Chen. 2021 · 2021
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Searching to sparsify tensor decomposition for n-ary relational data
Shimin Di, Quanming Yao, and Lei Chen. 2021 · 2021
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Knowledge hypergraphs: prediction beyond binary relations
Bahare Fatemi, Perouz Taslakian, David Vazquez, and David Poole. 2021 · 2021
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Link prediction on n-ary relational data based on relatedness evaluation
Saiping Guan, Xiaolong Jin, Jiafeng Guo, Yuanzhuo Wang, and Xueqi Cheng. 2021 · 2021
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A survey on knowledge graphs: Representation, acquisition, and applications
Shaoxiong Ji, Shirui Pan, Erik Cambria, Pekka Marttinen, and S Yu Philip. 2021 · 2021
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Nicolas Hubert, Pierre Monnin, and Heiko Paulheim. 2023 · 2023
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On the evolution of knowledge graphs: A survey and perspective
Xuhui Jiang, Chengjin Xu, Yinghan Shen, Xun Sun, Lumingyuan Tang, Saizhuo Wang, Zhongwu Chen, Yuanzhuo Wang, and Jian Guo. 2023 · 2023
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Graph-based non-sampling for knowledge graph enhanced recommendation
Shuang Liang, Jie Shao, Jiasheng Zhang, and Bin Cui. 2023 · 2023
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Self-supervised dynamic hypergraph recommendation based on hyper-relational knowledge graph
Yi Liu, Hongrui Xuan, Bohan Li, Meng Wang, Tong Chen, and Hongzhi Yin. 2023 · 2023
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A survey on few-shot knowledge graph completion with structural and commonsense knowledge
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Role-aware modeling for n-ary relational knowledge bases
Yu Liu, Quanming Yao, and Yong Li. 2021 · 2021
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Knowledge graph embedding for link prediction: A comparative analysis
Andrea Rossi, Denilson Barbosa, Donatella Firmani, Antonio Matinata, and Paolo Merialdo. 2021 · 2021
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Reta: A schema-aware, end-to-end solution for instance completion in knowledge graphs
Paolo Rosso, Dingqi Yang, Natalia Ostapuk, and Philippe Cudré-Mauroux. 2021 · 2021
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Improving hyper-relational knowledge graph completion
Donghan Yu and Yiming Yang. 2021 · 2021
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A survey on temporal knowledge graphs-extrapolation and interpolation tasks
Sulin Chen and Jingbin Wang. 2022 · 2022
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Explainable link prediction in knowledge hypergraphs
Zirui Chen, Xin Wang, Chenxu Wang, and Jianxin Li. 2022 · 2022
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Comprehensive analysis of knowledge graph embedding techniques benchmarked on link prediction
Ilaria Ferrari, Giacomo Frisoni, Paolo Italiani, Gianluca Moro, and Claudio Sartori. 2022 · 2022
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Haodi Ma and Daisy Zhe Wang. 2023 · 2023
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What is a multi-modal knowledge graph: A survey
Jinghui Peng, Xinyu Hu, Wenbo Huang, and Jian Yang. 2023 · 2023
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Llama: Open and efficient foundation language models
Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, et al. 2023 · 2023
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Kicgpt: Large language model with knowledge in context for knowledge graph completion
Yanbin Wei, Qiushi Huang, Yu Zhang, and James Kwok. 2023 · 2023
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Shrinking embeddings for hyper-relational knowledge graphs
Bo Xiong, Mojtaba Nayyer, Shirui Pan, and Steffen Staab. 2023 · 2023
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Exploring large language models for knowledge graph completion
Liang Yao, Jiazhen Peng, Chengsheng Mao, and Yuan Luo. 2023 · 2023
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Knowledge graph embedding: A survey from the perspective of representation spaces
Jiahang Cao, Jinyuan Fang, Zaiqiao Meng, and Shangsong Liang. 2024 · 2024
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Knowledge graph embedding: An overview
Xiou Ge, Yun Cheng Wang, Bin Wang, C-C Jay Kuo, et al. 2024 · 2024
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Hypermono: A monotonicity-aware approach to hyper-relational knowledge representation
Zhiwei Hu, Víctor Gutiérrez-Basulto, Zhiliang Xiang, Ru Li, and Jeff Z Pan. 2024 · 2024
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Causallp: Learning causal relations with weighted knowledge graph link prediction
Utkarshani Jaimini, Cory Henson, and Amit P Sheth. 2024 · 2024
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Zero-shot link prediction in knowledge graphs with large language models
Mingchen Li, Chen Ling, Rui Zhang, and Liang Zhao. 2024b · 2024
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A survey of knowledge graph reasoning on graph types: Static, dynamic, and multi-modal
Ke Liang, Lingyuan Meng, Meng Liu, Yue Liu, Wenxuan Tu, Siwei Wang, Sihang Zhou, Xinwang Liu, Fuchun Sun, and Kunlun He. 2024 · 2024
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Hypercl: A contrastive learning framework for hyper-relational knowledge graph embedding with hierarchical ontology
Yuhuan Lu, Weijian Yu, Xin Jing, and Dingqi Yang. 2024 · 2024
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Survey on embedding models for knowledge graph and its applications
Manita Pote. 2024 · 2024
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In-context learning with topological information for llm-based knowledge graph completion
Udari Madhushani Sehwag, Kassiani Papasotiriou, Jared Vann, and Sumitra Ganesh. 2024 · 2024
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Mhre: Multivariate link prediction method for medical hyper-relational facts
Weiguang Wang, Xuanyi Zhang, Juan Zhang, Wei Cai, Haiyan Zhao, and Xia Zhang. 2024 · 2024
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Few-shot link prediction on n-ary facts
Jiyao Wei, Saiping Guan, Xiaolong Jin, Jiafeng Guo, and Xueqi Cheng. 2024 · 2024
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Robust link prediction over noisy hyper-relational knowledge graphs via active learning
Weijian Yu, Jie Yang, and Dingqi Yang. 2024 · 2024
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Making large language models perform better in knowledge graph completion
Yichi Zhang, Zhuo Chen, Lingbing Guo, Yajing Xu, Wen Zhang, and Huajun Chen. 2024 · 2024
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Inductive link prediction in n-ary knowledge graphs
Jiyao Wei, Saiping Guan, Xiaolong Jin, Jiafeng Guo, and Xueqi Cheng. 2025 · 2025
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Inductive link prediction on n-ary relational facts via semantic hypergraph reasoning
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