Federated Knowledge Graph Unlearning via Diffusion Model

Understand

Federated learning (FL) promotes the development and application of artificial intelligence technologies by enabling model sharing and collaboration while safeguarding data privacy.

• Knowledge graph (KG) embedding representation provides a foundation for knowledge reasoning and applications by mapping entities and relations into vector space.
• Federated KG embedding enables the utilization of knowledge from diverse client sources while safeguarding the privacy of local data.
• However, due to demands such as privacy protection and the need to adapt to dynamic data changes, investigations into machine unlearning (MU) have been sparked.