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A Survey on Temporal Knowledge Graph: Representation Learning and Applications
March 11, 2024, 4:47 a.m. | Li Cai, Xin Mao, Yuhao Zhou, Zhaoguang Long, Changxu Wu, Man Lan
cs.CL updates on arXiv.org arxiv.org
Abstract: Knowledge graphs have garnered significant research attention and are widely used to enhance downstream applications. However, most current studies mainly focus on static knowledge graphs, whose facts do not change with time, and disregard their dynamic evolution over time. As a result, temporal knowledge graphs have attracted more attention because a large amount of structured knowledge exists only within a specific period. Knowledge graph representation learning aims to learn low-dimensional vector embeddings for entities and …
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