Research on the Construction of a Knowledge Graph for Decision-making on Compliance With Restrictive Measures and Countermeasures Against Illegal Sanctions in the Russian Natural Gas Industry Based on the Deepseek Ai Model
Year: 2025
Type: article
Abstract: 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.
Source: Herald of V.A. Musin Law Center
DOI: 10.61525/s0035542-6
Author: Gao Yu
Institution: Tsinghua University
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4412928985