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Apr 3, 2020 · We propose COTSAE that combines the structure and attribute information of entities by co-training two embedding learning components, respectively.
To solve these problems, we propose COTSAE that combines the structure and attribute information of entities by co-training two embedding learn- ing components, ...
This work proposes COTSAE that combines the structure and attribute information of entities by co-training two embedding learning components, respectively, ...
Yang K, Liu S, Zhao J, Wang Y, Xie B. COTSAE: co-training of structure and attribute embeddings for entity alignment, in Proceedings of the AAAI Conference ...
The implement of "COTSAE: CO-Training of Structure and Attribute Embeddings for Entity Alignment" 14 stars 2 forks
COTSAE: "COTSAE: CO-Training of Structure and Attribute Embeddings for Entity Alignment". Kai Yang, Shaoqin Liu, Junfeng Zhao, Yasha Wang, Bing Xie. (AAAI ...
Jun 6, 2022 · We summarize the process of. Embedding-based EA as the following three steps: (i) taking two input KGs and collecting seed alignment as training ...
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Jun 25, 2024 · Entity alignment aims to construct a complete knowledge graph (KG) by matching the same entities in multi-source KGs.
Jan 25, 2022 · Abstract. Entity alignment aims at integrating heterogeneous knowledge from different knowledge graphs.
To solve this problem, Yang et al. [26] proposed the COTSAE model, which combines structural and attribute information associated with entities by co-training ...