2022
AAAI
AAAI 2022
Evaluating Explanations of Relational Graph Convolutional Network Link Predictions on Knowledge Graphs
Abstract
Abstract 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.
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Interdisciplinary Bridge
— Deep Learning and Knowledge & Reasoning and Machine Learning
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Keyword Pioneer
— scoring metrics
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio