A Comprehensive Survey of Few-shot Information Networks

Information networks store rich information in the nodes and edges, which benefit many downstream tasks, such as recommender systems and knowledge graph completion. Information networks contain homogeneous information, heterogeneous information and knowledge graphs. A significant number of surveys focus on one of the three parts and summarize the research works, but few surveys conclude and compare the three kinds of information networks. In addition, in real scenarios, lots of information networks lack sufficient labeled data, so the combination of meta-learning and information networks can bring in extended applications. This paper concentrates on few-shot information networks and systematically presents recent works to help analyze and follow related works.