A survey of graph unlearning

Summary

A survey paper presents the first systematic review of graph unlearning, which removes sensitive data traces from trained graph models. It offers a taxonomy and literature overview, explains core concepts and evaluation measures, and covers applications in social networks, recommender systems and Internet of Things settings. It also identifies promising research directions.