TY - CONF

T1 - An Intelligent Assistant for Working with Regulatory Documents Based on Ontological Modeling and RAG

AU - Grekhova, Anastasiya

AU - Palchunov, Dmitry

AU - Shishkin, Alexander

AU - Zaitsev, Alexander

N1 - A. Grekhova, D. Palchunov, A. Shishkin and A. Zaitsev, "An Intelligent Assistant for Working with Regulatory Documents Based on Ontological Modeling and RAG," 2025 IEEE XVII International Scientific and Technical Conference on Actual Problems of Electronic Instrument Engineering (APEIE), Novosibirsk, Russian Federation, 2025, pp. 1-6, doi: 10.1109/APEIE66761.2025.11289384.

PY - 2025/11/14

Y1 - 2025/11/14

N2 - The increasing volume of regulatory documentation in construction and engineering complicates decision-making and raises the risk of errors and non-compliance. Existing search systems fail to provide sufficient semantic understanding of user needs, while large language models suffer from hallucinations and incomplete answers. This paper presents a hybrid intelligent assistant that integrates retrieval-augmented generation, ontological modeling, and multi-agent architecture to address these limitations. The system extracts entities and situations from regulatory documents to build an ontological domain model, enabling both semantic interpretation and automated consistency verification of generated responses. Vector similarity measures are combined with concept-level ontological relationships to improve retrieval accuracy. A multi-agent architecture ensures modularity and scalability, supporting document analysis, query history tracking, personalized response generation based on user context, and precise reference linking to primary sources. The proposed approach is evaluated in the construction domain, where practitioners must simultaneously consider standards at multiple regulatory levels. The practical contribution lies in reducing compliance costs and risks while increasing efficiency in handling complex multi-level regulatory frameworks. Future research will focus on cross-domain implementation and comprehensive evaluation of system performance.

AB - The increasing volume of regulatory documentation in construction and engineering complicates decision-making and raises the risk of errors and non-compliance. Existing search systems fail to provide sufficient semantic understanding of user needs, while large language models suffer from hallucinations and incomplete answers. This paper presents a hybrid intelligent assistant that integrates retrieval-augmented generation, ontological modeling, and multi-agent architecture to address these limitations. The system extracts entities and situations from regulatory documents to build an ontological domain model, enabling both semantic interpretation and automated consistency verification of generated responses. Vector similarity measures are combined with concept-level ontological relationships to improve retrieval accuracy. A multi-agent architecture ensures modularity and scalability, supporting document analysis, query history tracking, personalized response generation based on user context, and precise reference linking to primary sources. The proposed approach is evaluated in the construction domain, where practitioners must simultaneously consider standards at multiple regulatory levels. The practical contribution lies in reducing compliance costs and risks while increasing efficiency in handling complex multi-level regulatory frameworks. Future research will focus on cross-domain implementation and comprehensive evaluation of system performance.

KW - нормативные документы

KW - интеллектуальный ассистент

KW - онтологическое моделирование

KW - семантический поиск

KW - Retrieval-Augmented Generation (RAG)

KW - мультиагентные системы

KW - автоматизация обеспечения соответствия требованиям

KW - Regulatory documents

KW - intelligent assistant

KW - ontological modeling

KW - semantic search

KW - Retrieval-Augmented Generation

KW - multi-agent systems

KW - compliance automation

UR - https://www.scopus.com/pages/publications/105031772907

U2 - 10.1109/APEIE66761.2025.11289384

DO - 10.1109/APEIE66761.2025.11289384

M3 - Paper

SP - 1

EP - 6

T2 - 2025 IEEE XVII International Scientific and Technical Conference on Actual Problems of Electronic Instrument Engineering (APEIE)

Y2 - 14 November 2025 through 16 November 2025

ER -