Deep Learning for Learning Graph Representations

January 3, 2020 Abstract Mining graph data has become a popular research topic in computer science and has been widely studied in both academia and industry given the increasing amount of network data in the recent years. However, the huge amount of network data has posed great challenges for efficient analysis. The investigation on efficient representation of a graph has profound theoretical significance and important realistic meaning, we therefore introduce some basic ideas in graph representation/network embedding as well as some representative models in this chapter. Keywords: Deep Learning, Graph Representation, Network Embedding 1 Introduction Many real-world systems, such as Facebook/Twitter social systems, DBLP author-citation systems and roadmap transportation systems etc., can be formulated in the form of graphs or networks, making analyzing these systems equivalent to mining their corresponding graphs or networks. Literature on mining graphs or networks has two names: ...