Research on Knowledge Graph Completion Based upon Knowledge Graph Embedding

被引：1
|
作者：
Feng, Tuoyu [1 ]
Wu, Yongsheng [1 ]
Li, Libing [1 ]
机构：
[1] China Acad Elect & Informat Technol, China Elect Technol Grp Corp CETC, Beijing, Peoples R China
来源：
2024 9TH INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATION SYSTEMS, ICCCS 2024 | 2024年
关键词：
knowledge graph embeddings; knowledge graph completion; named entity recognition; knowledge representation;
D O I：
10.1109/ICCCS61882.2024.10603073
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
An essential first step in information representation and knowledge graph utilization is knowledge embedding. Knowledge graph completion (KGC) is a widely used technology to improve the accuracy and reliability of existing knowledge graphs by predicting the existence of relationships between the entities and supplementing the missing knowledge, which is the most significant knowledge graph embedding benchmarked challenge. In this paper, we have summarized the approaches of knowledge graph embedding and several main applications of KGE including link prediction, node classification, and temporal knowledge graph completion.
引用
收藏
页码：1335 / 1342
页数：8
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