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Abstract: Abstract This article discusses problems using the similarity operation corresponding to global similarity. Differences are noted in the carrying out of JSM-reasoning and JSM-research when solving problems using the similarity operation, corresponding to local and global similarity. PubDate: 2024-06-01 DOI: 10.3103/S0005105524700134
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Abstract: Abstract A fundamentally new possibility of obtaining additional information about the state of objects and processes of the subject area is considered. It is shown that wave processes can be investigated and analyzed through additional information obtained from the parameters of the functioning of the hardware elements of a computer information system. A method of revealing wave processes in a computer system is described. Experiments confirm the possibility of obtaining and using additional information from a secondary source for the information system to perform its regular functions. PubDate: 2024-06-01 DOI: 10.3103/S0005105524700122
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Abstract: The experience and specifics of the use of intelligent data analysis (IDA) in high-tech medical diagnostics are discussed. The current version of the IDA is a mathematical formalization of the so-called causal similarity heuristic by algebraic means. The main features and abilities of the developed approach are demonstrated in relation to the tasks of the diagnosis and treatment of certain types of human brain tumors. Some results characterizing the causality of the effect of pseudo-progression and tumor recurrence are presented. The potential and prospects of the developed approaches and diagnostic tools in the arsenal of modern evidence-based medicine are considered. PubDate: 2024-06-01 DOI: 10.3103/S0005105524700146
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Abstract: The article examines the evolution and current state of the data intensive sciences (DISs). The article focuses on approaches to methods of data mining generated by the development of artificial intelligence. It is noted that the rich opportunities of new approaches have caused unreasonable enthusiasm among scientists with respect to their capabilities, while the achieved level of knowledge is clearly ignored. It is shown how numerous facts of limited data processing potential have gradually accumulated without taking into account all previously established laws of nature and research methods. A significant role in the awareness of the real potential of working with data (including big data methods) was played by specialists in the field of methodology of science, who created a new direction, the epistemology of the DIS. Various ways and means of introducing expert knowledge at subsequent stages of analysis in the form of machine learning are listed. In sum, the appearance is noted of special algorithms for physically informed machine learning using data in combination with a traditional approach based on solving equations of mathematical physics. PubDate: 2024-06-01 DOI: 10.3103/S0005105524700109
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Abstract: Abstract Search strategies in the state space of knowledge bases in intellectual systems are considered. The directions of search from the initial data of the task to the goal and in reverse direction are shown. Rules and admissible moves leading to the goal in certain conditions of their application, when they become new search goals or subgoals, are analyzed. The problem-solving module is used as a search strategy for both data-driven and goal-driven search. It is shown that the choice of goal depends on the structure of the problem to be solved. The method of embedding the thesaurus into a probabilistic model for optimizing information retrieval is described. PubDate: 2024-06-01 DOI: 10.3103/S000510552470016X
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Abstract: This paper suggests the direction of the development of a systems approach to the development of information technology of intelligent decision-making support in the management of regional investment and construction projects. The technology under consideration represents conceptual and theoretical statements, language means of artificial intelligence, mathematical apparatus, algorithms, software, and mechanisms of machine learning, dialog communication, and the storage and processing of information, providing the solution of tasks set by the user. Drawing on the principle of compliance with the project management loops and the systemic understanding of the decision-making process, the composition and content of this technology are defined, and the scheme of its development is built. PubDate: 2024-06-01 DOI: 10.3103/S0005105524700158
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Abstract: In swarm algorithms, the need to measure population diversity arises in various contexts, such as in the adaptation of algorithm parameters, preventing the premature convergence of the algorithm and stopping and restarting it. Measures of population diversity allow the phases of the algorithm, namely, diversification and intensification, to be controlled. The article experimentally investigated six measures of population diversity of the optimization of the swallow swarm algorithm when solving the problem of optimizing the parameters of the membership functions of fuzzy classifiers. The resulting classifiers were tested on publicly available data sets drawn from the KEEL repository. PubDate: 2024-06-01 DOI: 10.3103/S0005105524700110
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Abstract: The paper proposes the use of a probabilistic knowledge-extraction mechanism to resume the use of good old-fashioned artificial intelligence. As a model task, it is proposed to automatically generate the rules of the Tic-Tac-Toe game. Similar rules were used in the well-known General Problem Solver system developed by A. Newell and H. Simon. Unlike the past, where scientists wrote the rules for the optimal game strategy manually, we will use a probabilistic-combinatorial formal method to generate them automatically. We will also discuss the relationship between the proposed approach and the reinforcement-learning paradigm. PubDate: 2024-04-01 DOI: 10.3103/S000510552470002X
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Abstract: — The concepts of a scientific library and a network scientific library are clarified. The role of scientific network libraries in solving issues of information support for scientific research and specific scientists is shown. It is noted that the Library of Natural Sciences of the Russian Academy of Sciences (BEN RAS) is a classic online scientific library, with more than 50 divisions. In this paper, the network technology of an automated library and information system (ALIS) is understood as a single automated library complex, which includes a geographically ungrouped system of terminals combined into a single system by means of connections, communication equipment, software, data transmission protocols, and control and computing tasks. The main requirements for network technologies include their ease of use; the ability to access other networks and systems and the internet; high data transfer speed; and high information security. The generations of the development of the ALIS are considered, and it is noted that the attention is attracted by open source ALIS. The basic principles of building an ALIS network library are formulated, which are presented in the form of three blocks: methodological, technological, and linguistic. A general model of network ALIS has been developed using the example of BEN RAS, which includes the main technological blocks: management of all processes; acquisition of information funds; processing of all information resources entering the AIS and resources of its own generation; storage of information resources: traditional and electronic, to be stored and used in information service processes; and user services. The key connecting element is the information need both for the formation of information resources included in the ALIS and for the organization of an information support system for scientific research. The peculiarities of the network structure are that the information support unit uses different classification systems and different levels of categorization to match user requests more accurately, whereas the formation of information arrays takes place, as a rule, at the upper level of one or another classification system chosen as the main one. PubDate: 2024-04-01 DOI: 10.3103/S0005105524700092
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Abstract: — A cluster analysis of the 100 most cited scientific papers on bibliometrics (scientometrics and informetrics) is carried out. The main bibliometric methods are identified, which make it possible to distinguish between the subject areas of their application. Co-citation of scientific papers and co-citation of their authors are still common. The analysis of scientific vocabulary (co-occurrence of words) complements the noted techniques. More often, in recent years, a set of bibliometric methods is used as a result of the application of modern computer programs to the statistical processing of bibliographic data. The fields of development and the application of bibliometrics related to separate clusters include nonmatching groups of various research topics in combination with different bibliometric methods. The use of bibliometrics in soft science (such as the social sciences) research is widespread, and in recent years it has not come at an inferior rate to its more traditional use in the natural sciences. The statistics on documents, references, and other indicators, to some extent, form the soft sciences themselves and delineate the areas of relevant studies. PubDate: 2024-04-01 DOI: 10.3103/S0005105524700055
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Abstract: To unify the understanding of and improvements to management efficiency, the conceptual apparatus of information support for risk management of BP is clarified, and methods of analysis and assessment of risk in the information environment are explored, using the example of a metallurgical company. The development of economic and mathematical support in calculating a quantitative measure of risk is presented, and a matrix for calculating the correction weight coefficient Wi for the determination if this measure is proposed, which allows us to take into account the duration and importance of identified risk factors, rank risks, and make informed decisions based on a more complete and detailed assessment of them. PubDate: 2024-04-01 DOI: 10.3103/S0005105524700018
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Abstract: In this paper, we propose techniques to improve the efficiency of systems acting with knowledge bases and based on functional neural networks (FN-networks) formalism due to the use of their structural features. The article addresses the case of partially defined FN-networks, which have a regular structure and are set as lists of multiple similar objects and fragments with common structure such that their number is unknown and may be unlimited. It offers an algorithm to find solution, which is based on dynamic formation of limited, fully determined local fragments of partially defined network and subsequent transfer of the results to the entire FN-network, which may be endless. PubDate: 2024-04-01 DOI: 10.3103/S0005105524700067
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Abstract: An approach to implementing perceptual-cognitive interfaces (PCIs) is presented in the context of the synchronous transmission of speech messages with perceptual semantics via technologically available and relevant sensory channels (visual, auditory, tactile, olfactory, and motor). The architecture of interfaces, implementation of the language model, and limitations imposed by the PCI model are considered. The introduction of the term “sensory technolinguistics” is justified, and possible areas of using perceptual-cognitive interfaces are described. PubDate: 2024-04-01 DOI: 10.3103/S0005105524700079
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Abstract: Some possible mathematical models and methods of intelligent data analysis (IDA) for the field of evidence-based medicine (EBM) are discussed. Two critically significant limitations for the application of traditional (statistics-based) EBM approach are considered: work with open subject areas and with small (statistically nonsignificant) collections of analyzed data. A special class of IDA methods based on the computer-oriented formalization of causal similarity heuristics using logical and algebraic means is presented. Options for clarifying the concept of evidence-based are proposed, which allow the indicated limitations of the traditional EBM approach to be circumvented. Some practically significant characteristics of this variant of the use of artificial intelligence methods in the tasks of evidence-based medicine are discussed. PubDate: 2024-04-01 DOI: 10.3103/S0005105524700031
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Abstract: — Three main stages in the approach to identifying news on natural disasters and the clustering groups of citizens are considered. The first step presents the sequence of performing several natural language processing tasks. The problem of the ambiguity and vagueness of news similarities has been ignored in traditional methods of event detection. To this end, the second step is to apply fuzzy set techniques to the events extracted to improve the quality of clustering and to eliminate the vagueness of the extracted information. A certain degree of hazard is then entered as input to the citizen clustering method to identify communities that feature similar degrees of distress. The results show that with the help of the proposed approach, it is possible to identify homogeneous and compact clusters of citizens. PubDate: 2024-04-01 DOI: 10.3103/S0005105524700080
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Abstract: This article discusses the importance of the timely receipt and analysis of information on the likelihood of competitors producing similar products, especially for military and dual-use products. Methods of information collection are considered. The main form of information collection is monitoring. By processing information about direct and indirect competitors, both open and closed, specialists in Russian enterprises and companies, knowing the weaknesses and strengths of their competitors, change their production process over time. The main characteristic of the information system for obtaining and processing data is bandwidth, as the system that can provide more bandwidth wins the competition. That is, one criterion for the competitiveness of any system is the bandwidth of its information channel. The process of forming the levels of hierarchy of the information system is considered. The importance of information systems in the modern economy is noted, as in a business where new competitors are constantly emerging, maintaining one’s market position requires constant attention. PubDate: 2024-04-01 DOI: 10.3103/S0005105524700043
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Abstract: Hierarchical, descriptive, and faceted methods of constructing knowledge classifiers and also the classification of knowledge using folksnomies are described. Mathematical models to formalize the listed methods of constructing classifiers are presented. A general description of the classifiers of the Russian Science Citation Index, Code of State Categories Scientific and Technical Information, and Universal Decimal Classification is given. The Chinese experience of classifying scientific publications and the American experience of classifying patent documents are analyzed. An alternative possibility for classifying scientific publications using clustering with bibliometric indicators and using keywords is indicated. A review of the main methods and means of comparing knowledge classifiers using qualifiers and expert competencies is carried out. A new approach to the compilation of knowledge classifiers based on their reduction to oriented trees and the construction of homomorphisms between these graphs is proposed. PubDate: 2024-02-01 DOI: 10.3103/S0005105524010084
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Abstract: — This work is devoted to the development of a modification of the particle collision algorithm (PCA), which provides an approximate solution to the traveling salesman problem. The resulting modification was tested on a number of well-known tasks and demonstrated greater accuracy and efficiency than its analogues. PubDate: 2024-02-01 DOI: 10.3103/S0005105524010047
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Abstract: — Trends in the implementation of digital twins (DTs) of real-world objects for the effective and safe management of complex sociotechnical systems and processes have been identified. Their composition and their share of the IT market are discussed. The features of the formation of data centers on hardware and software platforms from the most well-known companies in the IT industry are considered. It is proposed that DT technologies be used in creating conditions for a high-quality and mobile educational process that takes into account the individual trajectories of personal growth of students. The concept of a digital student profile (DSP) is presented, which is convenient for obtaining a quick quantitative assessment of personal skills and abilities, which is convenient when entering the labor market. In an educational environment, DSPs can be used to analyze the academic achievements, behavior and needs of students. Criteria for the formation of DSPs as a multidimensional quantitative assessment are proposed. Using the example of the course Information Technologies in Science and Education, a criteria-based convolutional assessment of the mastery of the material covered is constructed, characterizing the achievements of a particular student, allowing the use of methods and means of data mining. The creation and application of DTs and DPSs is an important step in the development of a new paradigm of education, with the help of which it is possible to significantly improve the quality of learning and provide participants in the educational process with individual support and assistance in achieving their unique life goals. PubDate: 2024-02-01 DOI: 10.3103/S0005105524010096
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Abstract: The paper introduces a methodology for extracting opinion aspects from textual content by identifying the customer-evaluated parameters regarding a given object. These parameters form the foundation for shaping the customer’s attitudes toward the product or service. The proposed approach leverages topic modeling tools to delineate classes of vocabulary exhibiting semantics aligned with the parameters influencing the customer’s opinion about the object. Our study specifically explores the application of the BERTopic model as a topic modeling tool to address this challenge. The outlined methodology encompasses several sequential steps, including the preprocessing of textual data involving the removal of stopwords, conversion to lowercase characters, and lemmatization. Additionally, special consideration is given to the distinct lexical manifestations of opinion aspects, obtained as a result of the extraction of nominal, verbal, and adjectival single- and multicomponent phrases from the corpus. Subsequently, the corpus sentences are represented as vectors in a feature space expressed by the extracted words and phrases. The final step involves the application of topic modeling using the BERTopic model on the customer review corpus, utilizing the vector representations of corpus sentences. The experimental inquiry is conducted on a domain-specific Russian-language corpus comprising customer feedback on airline services gathered from customer review websites. The resultant topic distribution is then juxtaposed against a manually constructed conceptual model of the domain. The comparative analysis reveals that the automatic topic distribution aligns with the conceptual structure of the domain, demonstrating a precision of 0.955 and a recall of 0.875. These findings affirm the efficacy of employing the BERTopic model to address the problem of the corpus-based mining of opinion aspects. PubDate: 2024-02-01 DOI: 10.3103/S0005105524010060
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