Methods › General › Rule-based systems › Symbolic rule learning
Symbolic rule learning
Introduced by Simon Ott et al. in Scalable and interpretable rule-based link prediction for large heterogeneous knowledge graphs
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
Symbolic rule learning methods find regularities in data that can be expressed in the form of 'if-then' rules based on symbolic representations of the data.
Papers archive 2025-07-28
4 shown of 4, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
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pix2rule: End-to-end Neuro-symbolic Rule Learning 14 Jun 2021 · 3 repositories · arXiv:2106.07487
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Scalable and interpretable rule-based link prediction for large heterogeneous knowledge graphs 10 Dec 2020 · 1 repository · arXiv:2012.05750
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Discovering outstanding subgroup lists for numeric targets using MDL 16 Jun 2020 · 3 repositories · arXiv:2006.09186
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DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs 31 Oct 2019 · 1 repository · arXiv:1911.00055
Tasks archive 2025-07-28
10 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
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