Evaluating Explanations of Relational Graph Convolutional Network Link Predictions on Knowledge Graphs

No. 11: IAAI-22, EAAI-22, AAAI-22 Special Programs and Special Track, Student Papers and Demonstrations

Volume

Proceedings of the AAAI Conference on Artificial Intelligence, 36

The Twenty - Seventh AAAI / SIGAI Doctoral Consortium

Recently, explanation methods have been proposed to evaluate the predictions of Graph Neural Networks on the task of link prediction. Evaluating explanation quality is difficult without ground truth explanations. This thesis is focused on providing a method, including datasets and scoring metrics, to quantitatively evaluate explanation methods on link prediction on Knowledge Graphs.

10.1609/aaai.v36i11.21577