Research on Knowledge Graph Completion Based Upon Knowledge Graph Embedding

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.