Online Updates of Knowledge Graph Embedding A summary of the COMPLEX NETWORKS 2021 research paper by Luo Fei, Tianxing Wu, and Arijit Khan [Background: Knowledge Graphs and Embedding] Knowledge graph is a data model for complex networks to manage large-scale and real-world facts [1, 2]. Examples include DBpedia [3], YAGO [4], Freebase [5], NELL [6], personalized health knowledge graphs [7], etc., where a node represents an entity, and an edge denotes a relationship between two entities. Knowledge graph embedding [8, 9] is increasingly becoming popular, which aims to represent each relation and entity in a knowledge graph G as a d-dimensional vector, such that the original structure and relations in G are approximately preserved in this semantic space. KG embeddings are used in downstream applications, e.g., link prediction [10, 11, 12], entity classification [13], question answering [1, 14], KG completion [15], and recommender systems [16]. [Our Problem: Dynamic Updates in Kn