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View all- Gao S(2021)HyperEA: Hyperbolic Entity Alignment between Knowledge Graphs2021 4th International Conference on Artificial Intelligence and Big Data (ICAIBD)10.1109/ICAIBD51990.2021.9459046(550-554)Online publication date: 28-May-2021
Knowledge graphs are playing a crucial role in many machine learning applications. Since most of the knowledge graphs are far from complete, many knowledge graph completion models have been proposed. TransE and its extended models all model knowledge ...
Knowledge graph embedding aims to learn low-dimensional embedding vector representations for entities and relations, which can be used in further machine learning tasks. However, previous knowledge graph embedding models perform poorly when ...
We demonstrated the existence of a group algebraic structure hidden in relational knowledge embedding problems, which suggests that a group-based embedding framework is essential for designing embedding models. Our theoretical analysis explores merely ...
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