{"title":"On Modeling the Information Activities of Modern Libraries","authors":"I. V. Timoshenko","doi":"10.3103/S0005105524700195","DOIUrl":"10.3103/S0005105524700195","url":null,"abstract":"<p>The author formulates the principles and conditions for a comprehensive systemic representation of a library, based on the analytical description of its generalized functional model. The author presents a library model that combines both various local models of qualitative characteristics and quantitative methods of mathematical modeling. The author provides examples of the strict conclusions of the main quantitative indicators of library activity based on the data of the conceptual models of library activity described verbally.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 4","pages":"255 - 261"},"PeriodicalIF":0.5,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142413698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Developing a Knowledge Base from Oncological Patients’ Neurosurgical Operations Data","authors":"A. V. Amentes, M. I. Zabezhailo","doi":"10.3103/S0005105524700213","DOIUrl":"10.3103/S0005105524700213","url":null,"abstract":"<p>A case of working with real data from a medical institution to support diagnostic decisions is considered. Various approaches to solving the classification problem are discussed. The paper describes methods of separating patient data into positive and negative outcomes following operations and providing clear, interpretable, explainable, and trustworthy results. Examples of the work of the proposed JSM method on data are given with a demonstration of the result obtained.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 4","pages":"267 - 279"},"PeriodicalIF":0.5,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142413688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Population Diversity Management of Swallow Swarm Optimization Algorithm for Fuzzy Classification Problem","authors":"I. A. Hodashinsky","doi":"10.3103/S0005105524700110","DOIUrl":"10.3103/S0005105524700110","url":null,"abstract":"<p>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.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 3","pages":"182 - 187"},"PeriodicalIF":0.5,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Information Support for Decision-Making in the Management of Regional Investment and Construction Projects: A Systematic Approach","authors":"L. V. Rossikhina, D. E. Orlova, V. A. Chertov","doi":"10.3103/S0005105524700158","DOIUrl":"10.3103/S0005105524700158","url":null,"abstract":"<p>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.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 3","pages":"188 - 199"},"PeriodicalIF":0.5,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781253","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analysis of Detection of Empirical Regularity in Problems with a Similarity Operation Corresponding to Global Similarity","authors":"S. M. Gusakova","doi":"10.3103/S0005105524700134","DOIUrl":"10.3103/S0005105524700134","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 3","pages":"208 - 211"},"PeriodicalIF":0.5,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Search Strategies in the State Space of Knowledge Bases","authors":"N. I. Sidnyaev, Yu. I. Butenko, E. E. Sineva","doi":"10.3103/S000510552470016X","DOIUrl":"10.3103/S000510552470016X","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 3","pages":"212 - 224"},"PeriodicalIF":0.5,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781256","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Data-Intensive Science: Problems and Development of the Fourth Paradigm","authors":"A. O. Erkimbaev, V. Yu. Zitserman, G. A. Kobzev","doi":"10.3103/S0005105524700109","DOIUrl":"10.3103/S0005105524700109","url":null,"abstract":"<p>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.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 3","pages":"159 - 171"},"PeriodicalIF":0.5,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Method of Obtaining Additional Information Based on the Study of Wave Phenomena in the Hardware Part of the Information System for Managing Objects of the Subject Area","authors":"V. N. Shvedenko, D. S. Alekseev","doi":"10.3103/S0005105524700122","DOIUrl":"10.3103/S0005105524700122","url":null,"abstract":"<div><p>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.</p></div>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 3","pages":"172 - 181"},"PeriodicalIF":0.5,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. I. Zabezhailo, M. A. Mikheyenkova, Yu. Yu. Trunin
{"title":"On the Nonbinary Version of the Causality Relation in the Intelligent Analysis of Oncological Data","authors":"M. I. Zabezhailo, M. A. Mikheyenkova, Yu. Yu. Trunin","doi":"10.3103/S0005105524700146","DOIUrl":"10.3103/S0005105524700146","url":null,"abstract":"<p>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.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 3","pages":"200 - 207"},"PeriodicalIF":0.5,"publicationDate":"2024-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141781254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. V. Avetisyan, D. V. Menyailov, A. P. Preobrazhensky
{"title":"Evaluating the Approach to Detecting and Monitoring Social Media Events to Combat Natural Disasters","authors":"T. V. Avetisyan, D. V. Menyailov, A. P. Preobrazhensky","doi":"10.3103/S0005105524700080","DOIUrl":"10.3103/S0005105524700080","url":null,"abstract":"<p>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.</p>","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"58 2","pages":"117 - 128"},"PeriodicalIF":0.5,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548976","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}