Dynamic graph embedding

Dynamic graph embedding is a technique that maps the structure of dynamic graphs into low-dimensional vector spaces, aiming to capture the evolving relationships and attributes of nodes over time. Its primary goal is to support various analytical tasks on graphs effectively through embedding representations, such as link prediction, node classification, and community detection. This technology has significant application value in areas like social network analysis, recommendation systems, and bioinformatics, enhancing the accuracy and efficiency of models.