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• METHODOLOGY FOR CONSTRUCTING AND EVALUATING AN ONTOLOGICAL PROFILE FOR CONTENT PERSONALIZATION SYSTEMS: STAGES AND EVALUATION CRITERIA

  Z.H. Mohammad

  248-262

  2025-12-30

  Abstract ▼

  This article presents the development and testing of a methodology for building an ontological profile designed for content personalization systems. It details the modular architecture of a web-based personalization system, illustrating the text processing and analysis methods and algorithms employed at each stage, and provides a step-by-step procedure for ontology creation. The methodology encompasses primary data processing, including the extraction of keywords and phrases, followed by their hierarchical clustering to reveal the semantic structure of the domain. Subsequent stages involve defining thresholds to filter out insignificant connections, and extracting and formalizing relationships between concepts using natural language processing techniques such as word-sense disambiguation and semantic similarity-based relationship extraction. An integrated pipeline was developed to implement this process, combining improved algorithms proposed by the author in previous studies, namely, an algorithm for extracting key phrases from individual text based on semantic similarity and a modified algorithm for word sense disambiguation. This pipeline also optimally integrated all necessary natural language processing tools, ensuring the efficient operation of these methods in the process of automatically constructing an ontology from text. The study places particular emphasis on a comprehensive evaluation of the resulting ontology using a specialized set of criteria designed to objectively assess the profile's quality, completeness, and consistency. A important component of the work is a computational experiment that clearly demonstrates the impact of each data processing stage on the final quality and efficacy of the ontology. The results show that the proposed method enables the construction of a practical, scalable, and relevant ontology, suitable for industrial deployment and integration into personalization systems to enhance their accuracy and adaptability

• 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.

• HYBRID BIOINSPIRED ALGORITHM FOR ONTOLOGIES MAPPING IN THE TASKS OF EXTRACTION AND KNOWLEDGE MANAGEMENT

  D.Y. Kravchenko, Y.A. Kravchenko, V. V. Markov

  2020-07-20

  Abstract ▼

  The article is devoted to solving the problem of mapping ontological models in the processes
  of extracting and knowledge management. The relevance and significance of this task are due to
  the need to maintain reliability and eliminate redundancy of knowledge during the integration
  (unification) of various origins structured information sources. The proximity and consistency of
  the conceptual semantics of the combined resource during the mapping is the main criterion for
  the effectiveness of the proposed solutions. The article considers the problems of choosing appropriate
  solution approaches that preserve semantics when displaying concepts. The strategy of
  choosing bio-inspired modeling is substantiated. The aspects of the effectiveness of various decentralized
  bio-inspired methods are analyzed. The reasons for the need for hybridization are identified.
  The paper proposes to solve the problem of mapping ontological models using a bio-inspired
  algorithm based on hybridization of bacterial and cuckoo search algorithms optimization mechanisms.
  The hybridization of these algorithms allowed us to combine their main advantages: a consistent
  bacterial search that provides a detailed study of local areas, and a significant number of
  the cuckoo agent during the implementation global movements of Levy flights. To evaluate the
  effectiveness of the proposed hybrid bio-inspired algorithm, a software product was developed and
  experiments were performed on the mapping of different sizes ontologies. Each concept of any
  ontology has a certain set of attributes, which is a semantic vector of attributes. The degree of the
  semantic vectors similarity for the compared concepts of displayed ontologies is a criterion for
  their integration. To improve the quality of the display process, a new encoding of solutions has
  been introduced. The quantitative estimates obtained demonstrate time savings in solving problems
  of relatively large dimension (from 500,000 ontograph vertices) of at least 13 %. The time
  complexity of the developed hybrid algorithm is O (n 2). The described studies have a high level of
  theoretical and practical significance and are directly related to the solution of classical problems
  of artificial intelligence aimed at finding hidden dependencies and patterns on a multitude of
  knowledge elements.

• AN ONTOLOGICAL APPROACH TO DISTRIBUTED COMPUTING TECHNOLOGIES IMPLEMENTATION ON THE INTERNET

  V. M. Kureichik , I.B. Safronenkova

  2020-11-22

  Abstract ▼

  Distributed computing technologies development has allowed uniting geographically distributed
  resources and has provided an opportunity for effective resource intensive problemsolving
  in various fields of science and technology. At the same time a set of problems, which demands
  the development of new approaches, taking into account contemporary Internet technologies
  implementation, has risen. In this paper a problem of workload relocation in distributed computer-
  aided design system (DCAD) operating in the “fog” environment was considered. The goal
  of this paper is ontological approach development to workload relocation problem-solving in
  DCAD taking into account some “fog” environment features. The ontological approach involves
  an ontological procedure implementation, which allows “filtering” the candidate-nodes, which
  have insufficient resources for workload relocation. The scientific novelty of this paper is ontological
  models using for workload relocation problem-solving in DCAD. It allows reducing the number
  of candidate-nodes in the “fog” for workload relocation, thereby contributing to reduce the
  time of location process modeling and, consequently, the total time of workload relocation problem-
  solving is also reduced. The fundamental difference of presented approach is domain
  knowledge, represented in ontological model, applying for workload relocation problem-solving.
  The experimental study results have shown the expediency of ontological analysis for workload
  relocation problem-solving .

• THE ESTIMATION OF CHANGING ENVIRONMENTAL CONDITIONS INFLUENCE ON THE WORKLOAD DISTRIBUTION IN THE UAV GROUP

  I.B. Safronenkova, A.B. Klimenko

  2021-12-24

  Abstract ▼

  The paper considers the problem of workload distribution in a group of unmanned aerial vehicles
  (UAVs) when monitoring a certain area in a changing environment, which has a direct impact on the
  onboard energy resources consumption. The stage of a monitoring problem-solving, which includes the
  distribution of UAVs over scanning bands, is described here. When this stage is carried, there is no
  opportunity to take into account the factors of environmental impact. But these factors are crucial
  due to the limited onboard energy resources. In this regard, a situation is very likely when the UAV is
  not able to complete the sub-task assigned to it, which jeopardizes the completion of the entire mission
  of the group. To avoid this situation, it is proposed to use the technique of a decision-making on
  the need to relocate the workload in a group of mobile robots (MR). The decision-making is based on
  the ontological analysis procedure, which allows limiting the number of choices for workload relocation.
  The ontology model of the workload distribution in a group of UAVs was developed. This model
  takes into account the possibility of additional performance involvement either by means of the resources
  of neighboring UAVs, or by means of devices of the "foggy" layer. Examples of production
  rules are given, on the basis of which a decision is made on the need to relocate the workload. A
  comparative estimation of the resources volume involved in the implementation of two methods of
  workload relocation problem solving, depending on the frequency of changes in environmental conditions,
  is carried out. The results of computational experiments have shown that the method based on
  ontological analysis is more efficient in comparison with the method based on LDG (Local Device
  Group) in terms of the amount of resources involved. This makes it possible to increase the time of joint
  mission implementation by the UAV group.

• THE USE OF DISTRIBUTIVE SEMANTICS IN THE IDENTIFICATION OF SIGNIFICANT COMBINATIONS OF TITLES OF SEVERAL TEXT COLLECTIONS IN THE FORMALIZATION OF LINGUISTIC EXPERT INFORMATION

  V.I. Danilchenko, V.M. Kureichik

  2022-08-09

  Abstract ▼

  The paper discusses methods of forming special models for the representation of various sets
  of knowledge in various information systems. The work is devoted to the application of distributive
  semantics in the identification of significant combinations in one subject area (PRO) within the
  framework of the formalization of linguistic expert information (LEI). The paper applies an approach
  to the formalization of LEI based on a set of analytical methods, where linear algebra is used as
  models. This approach makes it possible to initialize the procedure for the automatic formation of
  hierarchical architectures of LEI or dendrograms when identifying significant combinations of titles
  of several collections of texts. The scientific novelty lies in the proposed analytical approach using
  distributive semantics in identifying significant combinations of titles of several collections of texts,
  which allows for the analysis and processing of linguistic expert information. A distinctive characteristic
  of the proposed approach is the ability to formalize the ABM "Global Optimization Methods"
  based on the synthesis of various already existing hierarchies of the ABM under consideration. The
  paper aims to create conditions for the formalization of the LEI by applying distributive semantics
  when identifying significant combinations of titles of several collections. The practical value of the
  work lies in the development of a new approach to the formalization of LEI, taking into account distributive
  semantics when identifying significant combinations of titles of several collections of texts.
  The ontology in owl format "Methods of global optimization" in the program "Protege" is also built
  in the work. The ontology is built on the basis of related data about. The ontology constructed in this
  work complements the search structure within the framework of the considered PRO and can be
  supplemented and developed in the future.