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A Survey On Temporal Knowledge Graph Embedding - Models and Applications by william.shen35 is a document available to read on EtoBox.
This paper surveys temporal knowledge graph embedding (TKGE), a crucial technology for enhancing knowledge graph (KG) applications by integrating temporal data. It categorizes existing TKGE methods into seven classes, discusses their training processes, datasets, and evaluation schemes, and highlights challenges and future research directions. The review emphasizes the importance of effectively representing dynamic facts in KGs to improve logical reasoning and computational efficiency in various downstream
- Author
- william.shen35
- Language
- EN