Ontology Model Research Articles

Deformation mechanism and damage energy evolution of coal body under different gas pressures based on the energy principle

With increasing mining depth, the coal pillars of a coal mine will be in a stressful environment characterized by high gas pressures and unidirectional loading. To investigate the damage evolution characteristics and energy evolution mechanism of coal pillars loaded in a gas pressure environment, a uniaxial compression test was performed on a coal body under different gas pressures using a load testing apparatus for gas-containing coal rocks. The obtained results showed that the mechanical properties of the coal body varied with the gas pressure. Specifically, the peak strain, compressive strength, and elastic modulus decreased with increasing gas pressure; the higher the gas pressure, the lower the conversion rate of the elastic strain energy in the elastic deformation stage of the coal body and the lower its total input energy. With increasing gas pressure, the damage threshold of the coal body decreased, whereas the damage variable corresponding to the peak value, as well as the damage threshold value, increased. According to the theory of continuous damage mechanics, an ontological damage model of the coal body under different gas pressures was established based on the principle of minimum energy dissipation, and the rationality of the model was verified through a comparison between the theoretical and experimental data. Our findings can be useful in ensuring the safety of coal mining in terms of preventing gas disasters.

Digital Health Transformation: Leveraging a Knowledge Graph Reasoning Framework and Conversational Agents for Enhanced Knowledge Management

The research focuses on the limitations of traditional systems in optimizing information flow in the healthcare domain. It focuses on integrating knowledge graphs (KGs) and utilizing AI-powered applications, specifically conversational agents (CAs), particularly during peak operational hours in emergency departments (EDs). Leveraging the Cross Industry Standard Process for Data Mining (CRISP-DM) framework, the authors tailored a customized methodology, CRISP-knowledge graph (CRISP-KG), designed to harness KGs for constructing an intelligent knowledge base (KB) for CAs. This KG augmentation empowers CAs with advanced reasoning, knowledge management, and context awareness abilities. We utilized a hybrid method integrating a participatory design collaborative methodology (CM) and Methontology to construct a domain-centric robust formal ontological model depicting and mapping information flow during peak hours in EDs. The ultimate objective is to empower CAs with intelligent KBs, enabling seamless interaction with end users and enhancing the quality of care within EDs. The authors leveraged semantic web rule language (SWRL) to enhance inferencing capabilities within the KG framework further, facilitating efficient information management for assisting healthcare practitioners and patients. This innovative assistive solution helps efficiently manage information flow and information provision during peak hours. It also leads to better care outcomes and streamlined workflows within EDs.

Two senses of representation in science

Accounts of scientific representation typically assume that there is a single sense of “represent”, and they attempt to develop a theory that can account for all its features. The aim of this article is to draw the consequences of a distinction between two senses of “represent” that has been proposed recently. Taking inspiration from the distinction between speaker-meaning and expression-meaning in philosophy of language, a first sense is analysed in terms of the mental states of the user of a vehicle in context, and a second sense in terms of communal norms constraining contextual uses. I argue that making this distinction, and thus understanding the representation relation as essentially indexical and normative, can help us move beyond the controversies between various accounts of scientific representation, notably what have been dubbed informational and functional accounts, as well as debates regarding the ontology of scientific models.

Methods for semantic analysis of the state of the process of functioning of a system for detecting, preventing and eliminating the consequences of computer attacks

Objective. The aim of the study is to determine the most effective method of semantic analysis of the state of the process of detection, prevention and elimination of consequences of computer attacks. Method. The study was conducted based on the methods of semantic analysis of the state of the process of SOPKA operation. Result. A structural model of the system of semantic analysis of the state of the process of SOPKA operation is proposed, which is capable of providing an analysis of the state of the process of detection, prevention and elimination of consequences of computer attacks. The most effective method for solving the problem of semantic analysis of the state of the process of SOPKA operation is machine learning using ontological modeling. Conclusion. The results indicate the need for further research of the system of semantic analysis of the state of the process of detection, prevention and elimination of consequences of computer attacks.

A knowledge graph-based intelligent planning method for remanufacturing processes of used parts

Intelligent remanufacturing process planning is crucial for the efficient and high-quality remanufacturing of used parts with complex failure characteristics. However, due to the varied failure characteristics of used parts, the diversity of remanufacturing processes, and complex non-linear relationships among remanufacturing process elements, relying solely on mathematical programming or manual empirical is difficult to effectively model and optimise the remanufacturing process planning. To this end, a knowledge graph-based intelligent planning method for remanufacturing processes is proposed to enhance efficiency and quality by combining mathematical programming and knowledge reuse. Firstly, with failure characteristics as decision nodes, a full-element remanufacturing process ontology model is constructed, linking used parts, failure characteristics, and corresponding process plans. The BERT-BiLSTM-CRF model extracts remanufacturing process entities, and a remanufacturing process knowledge graph (RPKG) is constructed. Secondly, an intelligent decision-making model based on graph multi-node path retrieval is proposed. Aim to minimise carbon emissions, time, and cost, combining feature similarity calculations and nearest neighbour search (NNS) to efficiently retrieve the optimal process plan for each failure characteristic. Then, the optimal process plans are merged based on process constraints to create the complete plan. Finally, a concrete case is given to verify the effectiveness and advantages of this method.

Interweaving academic insights: advancing university knowledge management through a strategic data fabric framework

PurposeEffective knowledge management in large academic institutions is crucial for fostering innovation and improving educational practices. However, these institutions often face challenges, such as data fragmentation, siloed information systems and the complexity of integrating different data sources from various departments with complex hierarchical structures. To address these problems, the authors proposed a data fabric strategic framework that improves and enhances knowledge management by leveraging ontologies and knowledge graphs. This study aims to investigate the potential of knowledge graphs, ontological knowledge modelling and knowledge representation to improve knowledge management in large academic institutions. It also describes how technology can enhance knowledge accessibility and exchanges and improve decision-making processes based on insights from complex educational systems.Design/methodology/approachThis study uses coordination theory as a foundational framework to analyse intricate data systems in preparation for constructing, the Wizard of Oz method to facilitate the systematic organisation and management of information and the execution of an ontology-based data fabric framework and knowledge graphs. The authors propose a data fabric strategic framework aimed at improving knowledge management by leveraging ontologies and knowledge graphs.FindingsThe final evaluation demonstrates that this approach effectively breaks down data silos, promotes research collaboration and improves decision-making processes in large academic settings, offering solution-oriented data fabric technologies applicable to universities and university federations globally.Practical implicationsThe proposed system provides a more efficient way of managing and connecting fragmented academic resources, improving accessibility for both learners and educators. By interconnecting and streaming knowledge management process, the system can reduce not only operational costs but also expenses on doing scientific research.Originality/valueAcademic institutions prioritise time efficiency when acquiring vital data for improved scientific results. This emphasis extends beyond data governance to focus on how collective intelligence might improve organisational performance. The academic community has enhanced data utilisation through the implementation of data fabric technologies to improve data accessibility and data line tracking.

Virtual simulators in the automated control system subsystem for training operators of metal-cutting machines

The article describes the proposed method of automated construction of virtual simulators for the subsystem of personnel training of the automated control systems of production. Its distinctive feature is the work with the customer based on the provision of functional videos from production, as well as the formalization of the design and development process in the form of structures for the process of creating software and visual modules taking into account the specifics of the development of virtual reality simulators. An ontological model has been developed for the construction of virtual simulators for training machine tool operators in the automated control systems of production, which uses the identified basic concepts and relationships between them in the subject area of work of machine tool operators. Its implementation is based on the Protege software environment. The following diagrams are proposed: functional and contextual IDEF0 of the functioning of virtual simulators for training in working on universal metal-cutting machines: milling and turning. The architecture of a virtual simulator for use in the subsystem of training personnel of automated control systems of production, as well as a structural diagram of the formation of practice-oriented skills in working on metal-cutting machines using virtual simulators are described.

An ontological model of the reproduction system of a mineral resource asset

One of the urgent problems in developing the subsoil mineral resource potential is the lack of reliable information on the volume of forecasted resources and the potential possibility of their transfer to conditional reserves for some types of mineral raw materials. The heterogeneity and diversity of information sources sometimes makes it impossible to create a model of a single information repository with its attributes and connections. The traditional approach to organizing an information storage system based on a relational database cannot be applied in this situation. Therefore, it is urgent to find an alternative to both the data storage system itself and the approaches that are used in its filling and updating. We propose to use an ontological model to solve this problem, as a way to organize a storage system and systematize heterogeneous sources of information. At the same time, taking into account a fairly large number of alternative options for constructing an ontological model, we propose to base it precisely on the concept of mineral resource potential.

An ontology to describe the damage process to built cultural heritage triggered by earthquakes: The CHEDO model

Information on cultural heritage is critical both to understand its value and to support management. Collecting, managing, visualizing, and sharing this information requires standardization. In the last decades, architecture has advanced in information management with the implementation of Building Information Modelling (BIM) methodology. The application of this methodology to cultural heritage has associated challenges due to the complexity and heterogeneity of the information. The integration of ontologies and BIM allows obtaining semantically enriched digital models, which has led to a growing interest in the field of architectural cultural heritage. In this article, the Cultural Heritage Earthquake Damage Ontology (CHEDO) model is presented. This ontology has been designed to document damage and loss caused by earthquakes in cultural heritage, through its integration into BIM systems interconnected with databases, although this integration is not addressed in the present work. The CHEDO model integrates terms and relationships to document the damage process in relation to the building characteristics (architectural, spatial, constructional, and geometrical) and the physical environment of the same. This model, by providing a comprehensive description of the building and its environment, allows for complete and accurate documentation of damage, which supports the planning of post-earthquake restoration and reconstruction. To facilitate interoperability with parallel ontologies in close domains of architectural cultural heritage, CHEDO was designed taking as reference the high-level ontology Conceptual Reference Model (CRM) developed by the International Committee for Documentation (CIDOC), of the International Council of Museums (ICOM). The proposed ontology is structured in four blocks: 'building and surrounding environment', to describe the building and its environment; 'building damage', to represent the damage and its causes; 'location', to describe the location of the building and the external processes; and 'terminology', to categorise and classify certain classes of the ontology.

Regional climatic changes and their impact on the level of avalanche hazard in East Kazakhstan.

The article examines the territory of East Kazakhstan, where a sharply continental climate prevails with hot summers, cold and snowy winters. The mountainous regions of East Kazakhstan are represented by the Kalba, Altai and Saur-Tarbagatay ranges, they are surrounded by rolling plains. The highest points are at 3000-4500m. On average, the heights are in the range of 900-1400m. Despite the low heights in the mountainous area, the problem of avalanche safety is acute in the region. At the same time, the situation is complicated by not always predictable weather events, the frequency of which is increasing every year. These include heavy precipitation, sometimes combined with a sharp warming in winter, and the changing wind regime of the territory. To identify regional climate changes and its connection with the avalanche-prone situation in the region, the study analyzed meteorological data from weather stations located directly near avalanche prone locations over the past 23 years since 2001, as well as data from observations of avalanche-prone areas since 2005 and information on registered spontaneous avalanches from 2013 to the present. This study is the first in the East Kazakhstan region, which presents the results of a comprehensive analysis of data on 497 avalanche-prone sites, of which 325 sites pose a threat to life and infrastructure. 10 most dangerous sites have been selected for detailed study. The analysis of climate data was carried out based on information from 7 weather stations. The article discusses the main climatic changes in the region, including an increase in air temperature, an increase in precipitation and a change in wind conditions. Data from weather stations and snow measuring routes covering the period since 2005 have been used to develop probabilistic avalanche forecasts. The use of statistical methods and the analysis of the relationships between meteorological parameters (temperature, precipitation, wind speed) made it possible to build models predicting avalanche-prone situations. Data on spontaneous avalanches were analyzed for five sites (Bogatyrevskaya site, Prokhodnaya, Sogornoye-Barlyk, Tainty and Pikhtovka). Based on these data, equations of dependence of temperature, wind and precipitation have been developed, which improves the accuracy of forecasting avalanche risks. An analysis of the data in the Statistica program showed a significant relationship between sudden warming, increased wind speed and precipitation, which precedes avalanches. Regression equations and the approximation confidence coefficient for the average values of the studied parameters are obtained. The results of the study make it possible not only to establish patterns, but also to propose effective methods for monitoring and forecasting avalanche hazard in the region. According to the data analysis, regional features of climate change in East Kazakhstan were identified, and a comparison was made with previously known works on Kazakhstan. The interrelation of climatic characteristics with avalanche hazard in the region is shown. The results obtained in the study will help us to better understand the regional manifestations of climate change. An important task for further forecasting of avalanche activity is the correct design of the avalanche collection database. The authors identified information objects (entities). An ontological database model (Entity Relationship Diagram) is constructed. Based on it, a database has been created for a system for monitoring and forecasting avalanche activity in the East Kazakhstan region.

Knowledge graph ontology model construction based on hierarchy structure and failure analysis for wind turbines

Knowledge graph ontology model construction based on hierarchy structure and failure analysis for wind turbines

Design of a Wearable Exoskeleton Piano Practice Aid Based on Multi-Domain Mapping and Top-Down Process Model.

This study designs and develops a wearable exoskeleton piano assistance system for individuals recovering from neurological injuries, aiming to help users regain the ability to perform complex tasks such as playing the piano. While soft robotic exoskeletons have proven effective in rehabilitation therapy and daily activity assistance, challenges remain in performing highly dexterous tasks due to structural complexity and insufficient motion accuracy. To address these issues, we developed a modular division method based on multi-domain mapping and a top-down process model. This method integrates the functional domain, structural domain, and user needs domain, and explores the principles and methods for creating functional construction modules, overcoming the limitations of traditional top-down approaches in design flexibility. By closely combining layout constraints with the design model, this method significantly improves the accuracy and efficiency of module configuration, offering a new path for the development of piano practice assistance devices. The results demonstrate that this device innovatively combines piano practice with rehabilitation training and through the introduction of ontological modeling methods, resolves the challenges of multidimensional needs mapping. Based on five user requirements (P), we calculated the corresponding demand weight (K), making the design more aligned with user needs. The device excels in enhancing motion accuracy, interactivity, and comfort, filling the gap in traditional piano assistance devices in terms of multi-functionality and high adaptability, and offering new ideas for the design and promotion of intelligent assistive devices. Simulation analysis, combined with the motion trajectory of the finger's proximal joint, calculates that 60° is the maximum bending angle for the aforementioned joint. Physical validation confirms the device's superior performance in terms of reliability and high-precision motion reproduction, meeting the requirements for piano-assisted training. Through multi-domain mapping, the top-down process model, and modular design, this research effectively breaks through the design flexibility and functional adaptability bottleneck of traditional piano assistance devices while integrating neurological rehabilitation with music education, opening up a new application path for intelligent assistive devices in the fields of rehabilitation medicine and arts education, and providing a solution for cross-disciplinary technology fusion and innovative development.

ТHE BEGINNING OF THE WORLD ACCORDING TO HESIODS AS THE BIRTH OF PHILOSOPHICAL ONTOLOGY

The work of Hesiod, an ancient Greek epic poet, is considered, in particular, his poem “Theogony”, as one of the first cosmogonic constructions in European culture. Particular attention is drawn to the image and concept of Chaos – the initial state of the world, which also has a creative, creative essence. The primary instances that appear together with Chaos – Gaia, Tartarus and Eros also act as elements of the basic ontological model. The attitude of the ancient philosophical tradition to the concept of Chaos, which was problematized even by the pre-Socratics and compared with the famous Orphic cosmologies, is analyzed. In this sense, the image of Chaos in Hesiod can be considered as the first principle of building the world by analogy with the search for arché in later philosophers, as well as in its abstract, idealized form – the initial theoretical model of being and the beginning of ancient ontology. Of particular interest in this sense is Chaos, a rather complex and mysterious reality that is primary in relation to others and, moreover, is itself a creative force. The problem can be formulated as follows: can Chaos in Hesiod’s poem be considered a mythological-poetic ontology, an analogue and prerequisite of the philosophical concept of being, or even a certain essence of the world, its eternal integral part. The task of the study is to describe a general approach to understanding Chaos in Hesiod’s poem as an ontological essential first principle, which serves as a prototype of the philosophical ontology of later philosophers. Chaos can be interpreted as the original state of being and as a reference system for all world coordinates and the ideal beginning of the world. The original, initial state of the world, as well as the origin of the latter, is a cross-cutting theme of ancient Greek philosophy and science. Already in the early theogony, in the Orphics and in Hesiod, we find a certain mythological-poetic and, at the same time, religious-philosophical model of the origin of the world and its first elements. It would be too bold to consider these rather fantastic images and constructions as a real philosophical or scientific theory, which already in the understanding of the ancient Greeks should have had clearly defined principles and a consistent logical structure. Nevertheless, already in the first attempts to describe the structure of the universe we see an attempt to find the beginning from which a kind of ontological intuition of ancient Greek philosophy begins and which will later lead to the emergence of the main philosophical schools. Moreover, this intuition allowed us to pose a question that is still the basis of ontological problems. Even a preliminary consideration of the historical-philosophical material demonstrates the possibility of various interpretations of the ontological constructions of early ancient cosmogonies. The vision of Chaos in Hesiod proposed here is the first step towards a hermeneutic reconstruction of the primary foundations of ancient Greek philosophy and its mythological and poetic origins.

Contextual Analysis of Financial Time Series

The evaluation of the financial state of small and medium-sized companies is a pressing issue today. This article introduces a novel method to evaluate a company’s financial state, implemented as a module within a decision support system. This component uses fuzzy logic and knowledge engineering methods. The article describes an ontological model that provides the framework for data analysis and financial time-series modeling. The ontological framework simplifies the representation of the trends in the financial indicators under analysis. Integrating an ontology and a set of fuzzy rules makes it possible to develop control systems based on fuzzy inference. This approach provides the analysis and interpretation of results. The experimental results validate the accuracy and effectiveness of the proposed method.

OPTIMIZING DISTRIBUTED DATA STORAGE IN MULTI-CLOUD ENVIRONMENTS: ALGORITHMIC APPROACH

Background. Multi-cloud environments present complex challenges in optimal resource allocation and provider selection. Previous research has established a comprehensive ontological model and evaluation criteria for distributed data storage, however efficient provider selection remains a significant challenge due to the dynamic nature of cloud services and the multitude of interdependent factors affecting performance and cost-effectiveness. Objective. The purpose of the paper is to develop and validate a sophisticated optimization function for cloud provider selection in multi-cloud environments, incorporating both Reinforcement Learning (RL) and Multi-Objective Evolutionary Algorithms (MOEAs) to address the complexity of provider selection while considering multiple competing objectives and constraints. Methods. The research employs an ontological approach to formalize domain concepts, relationships, and properties in multi-cloud environments. Additionally, an optimization function is developed incorporating multiple weighted criteria derived from the established ontological model. The study focuses on the implementation of the RL algorithm to adapt to dynamic changes in cloud provider characteristics and integration of MOEAs to handle multiple competing objectives as well as providing a comparative analysis with traditional selection methods and alternative optimization approaches for multi-cloud storage settings. Results. The proposed ontological model successfully formalizes the domain's concepts, relationships, and properties in multi-cloud environments. The optimization function demonstrates effectiveness in selecting the most suitable public cloud provider based on the proposed features, enhancing data management practices automation and decision-making processes. Conclusions. The developed optimization function and suggested methodology significantly advance the state-of-the-art in distributed multi-cloud data storage. The integration of RL and MOEAs provides a robust framework for addressing the complexity of multi-cloud environments while offering superior performance compared to existing approaches. The methodology successfully balances multiple objectives while adapting to dynamic changes in cloud provider characteristics.

An integrated framework for collaborative product design and assembly based on STEP compatible ontology model in cloud manufacturing

AbstractNowadays, new product development processes are encountering fast design and development cycles. This issue has become one the main competition factors among industries. Accordingly, companies make drastic efforts to enhance the quality and speed in the realm of designing and manufacturing by taking novel approaches. Using the potential of new technologies, they design and develop products worldwide, and integrate stakeholders in the collaborative process to achieve this goal. This study has aimed at laying a foundation to fulfill the requirements for globalized collaborative product development processes. This creates an opportunity for both an integrated and collaborative environment. As first objective, the paper has proposed STEP Standard-based model in the form of a cloud service model to create an integrated data structure for product design data while giving flexibility for service-oriented access to integrated model. For second objective, using the Ontology interoperability model, the collaborative design among the stakeholders has been enabled through smart interference control. This control interprets the data semantic to an ontology structure and detects the potential conflicts. The model supports two levels of parts in singular and collective form and based on the assembly scheme for collaborative design and development. Different facets of the proposed model are addressed to fulfill the necessity of real-time distributed collaboration in designing and assembling via a case study.

«“THE HARD ROAD TO GOODNESS»:” : IVAN FRANKO’S HUMANISTIC VISIONS

Franko’s literary work was a reflection of his spiritual impulses, experiences, interactions with his milieu, and the evolution of his worldview. The humanistic core of the writer’s creative thinking was always fundamentally centered on important anthropological issues. The paper focuses on his interpretation of the problem of good and evil. In Franko’s writings, the human quest for goodness aligns with the mythologem of the road. In his later works, this symbol acquires a transcendent determination and significant anthroposophical features, representing the complex path of a person toward goodness through inner struggle, catharsis, and spiritual insights. In his poems, goodness is revealed through various symbols, archetypes, characters, ontological models, anthroponyms, and theonyms. Semantically resonant images include spirit, heart, candle, God, love, prayer, light, work, truth, angel, demon, death, forgiveness, road, and river. The writer’s constant search for beauty and goodness always leads to the human heart — the epicenter of humanistic existence, serving as a person’s ontological, mental, and emotional core. As a writer, philosopher, and insightful expert on the human soul, Franko always believed in the triumph of humanity and goodness, which he considered the ‘universal ideal.’ Franko the humanist, whose existential program evolved under the influence of Christian ideas, national values, and folk pedagogy, aimed to affirm righteous human life through adherence to moral maxims, “so that the sum of goodness among people grows and continues to grow.” For the writer, the true essence of goodness is of utmost importance. It becomes attainable when human thoughts and actions are in harmony with moral principles. Franko’s humanism lies in his belief in the good person, the greatest ‘masterpiece of nature.’ The quintessence of the writer’s humanistic visions is most evident in the novellas “The Thorn in the Foot,” “How Yura Shykmaniuk Crossed the Cheremosh,” and the poetry collection “My ‘Izmaragd’.” Franko’s advocacy for goodness and “genuine human morality” extends from the fate of the individual to that of the nation and humanity, which must reach “the grand gates of statehood.” This is the singular and historically inevitable path that will lead the people out of age-old misfortune and ensure a stable national future.

System loophole of generalized noncontextuality

Generalized noncontextuality is a well-studied notion of classicality that is applicable to a single system, as opposed to Bell locality. It relies on representing operationally indistinguishable procedures identically in an ontological model. However, operational indistinguishability depends on the set of operations that one may use to distinguish two procedures: we refer to this set as the reference of indistinguishability. Thus, whether or not a given experiment is noncontextual depends on the choice of reference. The choices of references appearing in the literature are seldom discussed, but typically relate to an implicit notion of a system underlying the experiment. This shift in perspective then begs the question: how should one define the extent of the system underlying an experiment? This question depends in part on one's beliefs in the universe being fundamentally continuous or fundamentally composite. To draw a coherent picture of the possible approaches one may use, we start by formulating a notion of noncontextuality for prepare-and-measure scenarios with respect to an explicit reference of indistinguishability. We investigate how verdicts of noncontextuality depend on this choice of reference, and in the process we introduce the concept of the noncontextuality graph of a prepare-and-measure scenario. We then discuss several proposals that one may appeal to in order to fix the reference to a specific choice, and we relate these proposals to different conceptions of what a system really is. With this discussion, we advocate that whether or not an experiment is noncontextual is not as absolute as often perceived. Published by the American Physical Society 2024

Some Aspects of Interactive Simulation of Software Development with Integration of Ontological Models

Modern simulation technologies are of great importance, especially in those areas where errors in real processes can lead to significant costs and risks caused by the consequences of errors. The purpose of the article is to research of the interactive simulators in the field of software development with the integration of ontological models. The research methods are the main methodological approaches and technological tools for the development of interactive simulators in the field of software development with the integration of ontological models. Such methods, in particular, are: system and comparative analyzes – to identify the features of the creation and further use of interactive simulators in the field of software development with the integration of ontological models; the method of expert assessments, which involves the analysis of literary sources and information resources, conducting interviews and surveys of experts, the processes of development and testing of scalable and high-performance interactive simulators in the field of software development with the integration of ontological models. The novelty of the conducted research is the research of the possibility of integrating ontological models directly into the process of developing software simulated in interactive environments. The conclusion of the research carried out in the article is that the work was: the research was conducted on the use of simulation technologies in various subject areas; the role of interactive simulators is determined, which help the participants practice various scenarios in a virtual environment; development of critical thinking; improving decision-making skills; it is determined that interactive simulators are an important learning tool in the field of software development, where the integration of ontological models allows automating part of the processes and ensuring the standardization of procedures. Difficulties in implementing simulation training were identified: high initial costs and technical difficulties. For the successful integration of simulations, it is necessary to: provide a clear definition of educational goals (in particular, for the training of IT specialists); adapt simulations to the specific needs of the organization; integrate simulations into the general training program of IT specialists. It was determined that: ontological models play a key role in the improvement of interactive simulators, helping to structure and formalize knowledge in various subject areas; the use of ontologies contributes to the process of integration of various software components, thereby ensuring flexibility and scalability of systems.

Semantic Analysis of Natural Language Texts: Ontological Approach

The development of information (intelligent) learning systems, electronic document management systems, web-oriented systems working with text information in natural language has led to an increase in the volume of educational content and/or arrays of processed full-text documents. All this requires new means of organizing access to information, many of which should be classified as intelligent systems for knowledge processing. One of the effective approaches to identifying and processing the meaning of educational content (and/or text documents) is the use of ontologies. The purpose of the article is research, analysis of various approaches to determining the semantic content of texts in natural language, consideration of existing concepts of text analysis and prospects for using the proposed ontological approach to semantic analysis of texts in natural language. Research methods are methods of semantic analysis of the main concepts of the analyzed subject area (semantic analysis of texts in natural language). The article considers an approach to the linguistic analysis of texts based on ontological modeling. The novelty of the research is the application of the proposed ontological approach to the semantic analysis of texts in natural language to determine the meaning (semantics) of text information, which is used in intelligent systems of various classes. The conclusion of the research carried out in the article is as follows: an ontological approach to the semantic analysis of natural language text, its tasks and methods is proposed. The use of the proposed approach to text analysis leads to the understanding of semantic analysis as a single triad: <Ontology – Text – Meaning>. For effective and correct extraction of knowledge, it is suggested to use a multi-level ontology. The result of the interaction of a specific natural language text with an ontology is an ontological meaning – a set of interconnected subgraphs of the ontograph. The ontological content is extracted from the ontograph using a semantic analyzer. The dialogue processor examines the syntactic tree of sentence parsing (a connected element of the natural language text) and, based on the given question, finds a fragment in the text that is the answer to the question. Computer understanding (in information or intellectual systems) of natural language text is achieved, in particular, by: immersion of the text in a single environment of knowledge – ontology; formal presentation of meaning (semantics) in the knowledge base of the corresponding system; the possibility of operations on the ontological content. The proposed approach can be used to create intelligent information repositories that work in a single knowledge environment. The proposed approach to the semantic analysis of texts in natural language is focused on the automatic extraction of metadata from texts of various nature (for example, a text document, Internet content, educational content of relevant online courses, description of computer and board games). With further development of the proposed approach, it can be used in systems of automatic referencing of scientific publications, meaningful interpretation of multimedia content, training and testing (including elements of visual display of information and elements of gamification).