Rule learning with causal intervention for knowledge graph reasoning

Yuefeng He

doi:10.1016/j.asoc.2026.114802

Rule learning with causal intervention for knowledge graph reasoning

2026-02-12

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DOI：10.1016/j.asoc.2026.114802

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Abstract

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• Explicitly adopts causal intervention in a holistic rule learning framework for knowledge graph reasoning; • Models causality and confounders, and restores the connections between them to simulate causal intervention; • Decouples causality relations from confounders to acquire higher-quality rules; • Demonstrates the framework’s performance by performing experiments on five publicly available datasets.

Keywords:

causal intervention

knowledge graph reasoning

rule learning

confounders

holistic framework

Rule learning with causal intervention for knowledge graph reasoning

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