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Research uncovers a knowledge graph and decision-making tool for managing sanctions in the Russian gas industry, suggesting new cross-disciplinary integrations.
This article examines the pressure of Western restrictive measures and countermeasures affecting the Russian gas industry in the context of the Russian-Ukrainian conflict. It proposes a composite decision-support system that integrates a large language model (DeepSeek AI), knowledge graph technology, and a compliance reasoning algorithm. The construction of a compliance knowledge graph, encompassing sanction rules, corporate entities, and energy trade routes and augmented by a graph neural network mechanism, enables the intelligent identification of the impact of illegal sanction policies and the planning of responsive strategies. This study presents an "explainable and reasonable" framework of a sanctions and counter-sanctions graph that Chinese energy companies can use to anticipate the sanction-related risks they may encounter when cooperating with Russia, the Middle East, and Central Asia. At the same time, it introduces a compliance decision-making tool that deeply integrates language understanding capabilities of large models with a graph reasoning system, providing a cross-integration path for disciplines such as law, artificial intelligence, international relations, and energy economics in both China and Russia.
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Yu Gao (2025) studied this question.
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