eXpath: Explaining Knowledge Graph Link Prediction with Ontological Closed Path Rules
Summary: eXpath leverages ontological closed-path rules to produce semantically meaningful path-based explanations for embedding-based KG link prediction, moving beyond local single-link justifications. Improves explanation quality ≈20%, reduces explanation time 61.4%, and composes with single-link explainers. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Ye Sun (Beihang University)
- 2. Lei Shi (Beihang University)
- 3. Yongxin Tong (Beihang University)
BibTeX Citation
@article{sun_vldb25,
title = {{eXpath: Explaining Knowledge Graph Link Prediction with Ontological Closed Path Rules}},
author = {Sun, Ye and Shi, Lei and Tong, Yongxin},
journal = {PVLDB},
series = {{VLDB} '25},
volume = {18},
number = {9},
pages = {2818--2830},
doi = {10.14778/3746405.3746410},
url = {https://doi.org/10.14778/3746405.3746410},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 6 of 6 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 65 | Freebase: A Collaboratively Created Graph Database For Structuring Human Knowledge | 2008 | SIGMOD | 0.00038697603 |
| 1,057 | YAGO3: A Knowledge Base from Multilingual Wikipedias | 2015 | CIDR | 0.00012387149 |
| 4,832 | Association Rules with Graph Patterns | 2015 | VLDB | 6.4877e-05 |
| 6,295 | Explaining Link Prediction Systems based on Knowledge Graph Embeddings | 2022 | SIGMOD | 5.9231159e-05 |
| 7,330 | Discovering Association Rules from Big Graphs | 2022 | VLDB | 5.6435171e-05 |
| 7,413 | Kelpie: an Explainability Framework for Embedding-based Link Prediction Models | 2022 | VLDB | 5.624223e-05 |
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