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• SEMANTIC ANALYSIS AND INTEGRATION OF HETEROGENEOUS INFORMATION STREAMS IN DECISION SUPPORT SYSTEMS: A TECHNOLOGY REVIEW

  V. V. Gapochka , Е. Е. Polupanova

  2026-02-27

  Abstract ▼

  Modern decision support systems (DSS) increasingly rely on heterogeneous data streams from IoT sensors, databases, text messages, and social media, represented in different formats and characterized by diverse semantic models and quality levels. The lack of semantically aligned integration results in inconsistent entity interpretation, duplication, and loss of context, which reduces the quality and timeliness of decisions. The aim of this paper is to systematize methods for semantic analysis and integration of heterogeneous information streams in DSS and to identify their benefits, limitations, and application domains. The study is conducted as an analytical review of publications from 2018–2025 focusing on semantic interoperability, ontologies and knowledge graphs, multi-source data fusion, data federation, and real-time stream processing. The review shows that semantic compatibility is primarily achieved through ontologies and knowledge graphs that define shared entities and identifiers and provide a flexible integration schema. For real-time decision-making, hybrid solutions combining a semantic layer with data fusion algorithms and source trust assessment are the most effective; published case studies report accuracy gains of about 15–20% and response-time reductions of up to 70–80% in multi-source settings. For unstructured streams, NLP and machine learning play a key role by extracting entities and relations and enabling semantic enrichment. The results can be used to design DSS for smart city, industrial, and healthcare domains. Furthermore, the paper highlights the role of standards like SHACL for validation and SPARQL for querying, enhancing the practical applicability of semantic approaches. Future directions include automating ontology alignment to reduce labor costs and integrating with AI for dynamic adaptation to new data sources.

• FEATURES OF THE AGENT-MODULAR APPROACH APPLICATION IN THE DESIGN AND IMPLEMENTATION OF INFORMATION-COMPUTATIONAL SYSTEMS

  А.F. Zaytsev

  179-189

  2025-12-30

  Abstract ▼

  Information-computational systems play a key role in processing and analyzing large amounts of data, ensuring the efficient functioning of production, provision, as well as receipt of various digital goods and services. In the conditions of intellectualization and increasing diversity of functional requirements imposed on information systems, there is a need to develop new approaches for their construction and implementation. The paper considers the main features of the proposed agent-modular approach, which involves the construction of flexible and scalable information-computational systems capable of functioning in a distributed environment. The agent-modular approach is a methodological approach to the organization of information-computational systems based on the integration of system analysis methods, as well as agent and modular principle's of building various systems. The aim of the paper is to investigate theoretical and practical aspects of the application of the proposed agent-modular approach in building an information system, to analyze its advantages over other common approaches (object, component, service), and to present examples of its successful use. To achieve the set goal, it is necessary to solve the following tasks: – to research the theoretical foundations and identify the specific features of practical application of the proposed agent-modular approach; – to analyze the differences and describe the advantages of the proposed approach in its comparison with other approaches; – to present an example of building an information-computational system using the proposed approach. The following general scientific methods were used in the research process: decomposition, analysis, synthesis, comparison, description, formalization, structurization, modeling, design, as well as the basic principles of system, modular and agent-based approaches. Computers, and computing software tools were used as research materials. As a result of the study, the main theoretical and practical aspects of the proposed approach were considered. The agent-modular approach can be used to build various information systems at the stages related to their modeling and design. The proposed approach allows describing the structure, functioning, and interaction of various components of information-computational systems.