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Multi-modal entity alignment (MMEA) aims to discover identical entities across different knowledge graphs (KGs) whose entities are associated with relevant images.
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MRAEA: An Efficient and Robust Entity Alignment Approach for Cross-lingual Knowledge Graph. In WSDM . ACM, 420–428
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Molecular Contrastive Learning with Chemical Element Knowledge Graph. In AAAI . AAAI Press, 3968–3976
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ClusterEA: Scalable Entity Alignment with Stochastic Training and Normalized Mini-batch Similarities. In KDD . ACM, 421–431
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Meta-Learning in Neural Networks: A Survey
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Multi-modal Contrastive Representation Learning for Entity Alignment. In COLING . International Committee on Computational Linguistics, 2572–2584
Zhenxi Lin, Ziheng Zhang, Meng Wang, Yinghui Shi, Xian Wu, and Yefeng Zheng. 2022 · 2022
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Leveraging Multi-Modal Information for Cross-Lingual Entity Matching across Knowledge Graphs
Tianxing Wu, Chaoyu Gao, Lin Li, and Yuxiang Wang. 2022 · 2022
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Informed Multi-context Entity Alignment. In WSDM . ACM, 1197–1205
Kexuan Xin, Zequn Sun, Wen Hua, Wei Hu, and Xiaofang Zhou. 2022 · 2022
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A benchmark and comprehensive survey on knowledge graph entity alignment via representation learning
Rui Zhang, Bayu Distiawan Trisedya, Miao Li, Yong Jiang, and Jianzhong Qi. 2022 · 2022
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Semantics Driven Embedding Learning for Effective Entity Alignment. In ICDE . IEEE, 2127–2140
Ziyue Zhong, Meihui Zhang, Ju Fan, and Chenxiao Dou. 2022 · 2022
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Knowledge graph-enhanced molecular contrastive learning with functional prompt
Yin Fang, Qiang Zhang, Ningyu Zhang, Zhuo Chen, Xiang Zhuang, Xin Shao, Xiaohui Fan, and Huajun Chen. 2023 · 2023
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Revisiting Embedding-Based Entity Alignment: A Robust and Adaptive Method
Zequn Sun, Wei Hu, Chengming Wang, Yuxin Wang, and Yuzhong Qu. 2023 · 2023
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