Inductive Relation Prediction

Inductive Relation Prediction is a specific setting in the task of knowledge graph completion, which requires the model to predict relationships between entities on a completely new test graph that were not seen during the training phase. The goal of this task is to enhance the model's generalization ability so that it can handle unseen data, thereby playing a crucial role in dynamic and continuously expanding knowledge graphs. By performing Inductive Relation Prediction, the completeness and accuracy of knowledge graphs can be effectively improved, providing more reliable support for recommendation systems, information retrieval, natural language processing, and other fields.