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Explanation of Link Predictions on Knowledge Graphs via Levelwise Filtering and Graph Summarization
Published on 2024-05-3135 Views
Link Prediction methods aim at predicting missing facts in Knowledge Graphs (KGs) as they are inherently incomplete. Several methods rely on Knowledge Graph Embeddings, which are numerical representat
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Presentation
Explanation of Link Predictions on Knowledge Graphs via Levelwise Filtering and Graph Summarization00:00
Outline00:01
Context: Knowledge Graphs [7]00:20
Kelpie [10]: Explaining Link Predictions01:05
Kelpie: High-Level Architecture - 101:35
Kelpie: High-Level Architecture - 202:08
Kelpie: High-Level Architecture - 302:46
Goals02:57
Tackling Goals - 103:35
Semantic Pre-Filter03:43
Tackling Goals - 204:40
Quotient Explanation Builder04:58
Compute the quotient graph - Simulation05:26
Build Explanations from the Quotient06:11
Alternative quotients07:12
Solution 2: Bisimulation07:49
Solution 3: Depth-1 Bisimulation08:29
Experimental Setting09:09
Results: Necessary Relevance10:22
Results: Sufficient Relevance11:38
Results: cases of limited effectiveness11:51
Qualitative Evaluation12:49
Conclusions13:59
Thanks for the attention!14:44