AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS最新文献_第6页

Methods for the Automated Extraction of Program Parameters and Descriptions for Their Integration into Computing Systems 程序参数的自动提取方法及其与计算系统集成的描述

IF 0.4

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2026-09-11 DOI: 10.3103/S0005105526700652

T. V. Sannikov, A. N. Salnikov

{"title":"Methods for the Automated Extraction of Program Parameters and Descriptions for Their Integration into Computing Systems","authors":"T. V. Sannikov, A. N. Salnikov","doi":"10.3103/S0005105526700652","DOIUrl":"10.3103/S0005105526700652","url":null,"abstract":"This article addresses the problem of coordinating heterogeneous software tools in heterogeneous distributed application execution environments. Here, manually configuring launch parameters for newly installed programs on a computing cluster (such as command-line switches, environment variable values, and configuration file settings) poses significant challenges for domain researchers due to the large volume of utility information and the need to store and aggregate information in a fixed format. We propose a method for the automated extraction of launch parameters based on a hybrid neural network training architecture combining the generation of training samples using large language models with the subsequent fine-tuning of a compact transformer encoder. This approach eliminates the need for expensive graphics accelerators by applying the Low-Rank Adaptation (LoRA) technique to models with up to 1 billion parameters, enabling model execution (inference) on standard CPUs in control nodes. To formalize the quality of extraction, a two-component metric has been developed that aggregates the structural correctness of the output JSON schema (the presence of required fields and program parameter types in the obtained data) and the semantic accuracy of parameter values (correspondence with the description in the documentation). The experimental evaluation of the method focuses on a corpus of software package documentation (manual pages, README files). The design results confirm the possibility of approximating the documentation analysis process with a compact model, which contributes to the automation of the software deployment lifecycle and the reduction of task flow management errors in distributed computing systems.","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 3","pages":"S360 - S366"},"PeriodicalIF":0.4,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927568","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}

引用次数: 0

Construction and Annotation of a Russian-Language News Corpus for Automated Detection of Political Manipulation 面向政治操纵自动检测的俄语新闻语料库的构建与标注

IF 0.4

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2026-09-11 DOI: 10.3103/S0005105526700585

N. L. Kulyulina

{"title":"Construction and Annotation of a Russian-Language News Corpus for Automated Detection of Political Manipulation","authors":"N. L. Kulyulina","doi":"10.3103/S0005105526700585","DOIUrl":"10.3103/S0005105526700585","url":null,"abstract":"This paper addresses the challenge of developing specialized corpus resources for the automated analysis of political manipulation in Russian-language media discourse. Although semantic text analysis and computational discourse analysis have advanced substantially in recent years, most existing corpora and annotation schemes are designed for English-language data and do not adequately capture the linguistic and discursive characteristics of Russian-language news media. The objective of this study is to construct a specialized corpus of Russian-language news texts and to develop an annotation scheme tailored to the automated analysis of political manipulation, with explicit consideration of the linguistic and discursive features of the Russian-language media environment. The study introduces a corpus of sentence-level fragments extracted from Russian-language news texts published between 2010 and 2019, together with an annotation scheme for manipulative techniques. The scheme is based on an adaptation of established international classifications of manipulative strategies and is reduced to a limited set of interpretable techniques relevant to Russian-language news discourse. The proposed framework covers emotional, argumentative, and contextual forms of manipulative influence. The resulting corpus and annotation scheme provide an empirical foundation for the development and evaluation of automated methods for analyzing political manipulation in Russian-language news media and may also support further research in media and political discourse.","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 3","pages":"S307 - S311"},"PeriodicalIF":0.4,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927570","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}

引用次数: 0

On the Applicability of Neural Networks in the Publishing Industry 论神经网络在出版业中的适用性

IF 0.4

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2026-09-11 DOI: 10.3103/S0005105526700676

S. I. Shirinbegzoda, D. A. Shishkin, B. S. Usmanov, N. M. Borgest

{"title":"On the Applicability of Neural Networks in the Publishing Industry","authors":"S. I. Shirinbegzoda, D. A. Shishkin, B. S. Usmanov, N. M. Borgest","doi":"10.3103/S0005105526700676","DOIUrl":"10.3103/S0005105526700676","url":null,"abstract":"The paper assesses the limits of applicability of large language models in editorial tasks within the publishing process and identifies the optimal format of interaction between humans and algorithmic systems. The methodological basis of the study is a comparative experiment in which several popular neural network models—Alice AI, GigaChat, DeepSeek, Gemini, and ChatGPT—performed a statistical analysis of a control text in Russian. The quantitative characteristics of the text were determined: the number of words, characters with and without spaces, and the number of paragraphs. The obtained results were compared with reference values established using the MS Word text editor, which applies a deterministic character-counting algorithm. The results of the experiment showed that neural network models demonstrate varying degrees of accuracy when performing tasks of quantitative text analysis. The main reason for such errors lies in the architecture of large language models and the use of tokenization algorithms, which break the direct connection between characters and the model’s internal representation of the text. Based on the results obtained, the paper proposes the concept of a hybrid architecture for publishing information systems, in which generative language models are used to perform creative and analytical tasks, while operations requiring strict formal accuracy are assigned to specialized deterministic microservices. The proposed approach makes it possible to improve the reliability and predictability of intelligent publishing systems.","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 3","pages":"S376 - S380"},"PeriodicalIF":0.4,"publicationDate":"2026-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148927576","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}

引用次数: 0

Separation of Heat Flow Processes in the North Atlantic into Various Components and Their Analysis 北大西洋热流过程各分量的分离及其分析

IF 0.4

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2026-08-10 DOI: 10.3103/S0005105526700366

N. P. Tuchkova, K. P. Belyaev, G. M. Mikhaylov, K. A. Romashina

{"title":"Separation of Heat Flow Processes in the North Atlantic into Various Components and Their Analysis","authors":"N. P. Tuchkova, K. P. Belyaev, G. M. Mikhaylov, K. A. Romashina","doi":"10.3103/S0005105526700366","DOIUrl":"10.3103/S0005105526700366","url":null,"abstract":"The heat flux distribution in the North Atlantic calculated using a stochastic difference equation scheme, namely, a first-order autoregressive scheme with random coefficients, is studied. The ERA5 database, which contains geophysical data for the 40 years from 1979 to 2018, is used. The coefficients for the autoregressive series were previously determined based on these data, and it is shown that the conditions on the coefficients ensure the existence and uniqueness of a solution to this difference equation. The method for calculating distributions is based on successive integration using an autoregressive scheme. Computational experiments are conducted and analyzed. Moreover, it is shown that the theoretically calculated distributions are in good agreement with their empirical counterparts. Further, after the division of the original time series into a distinguished mean (trend) and a residual, the latter is analyzed as a stationary random process. Selected correlation functions were calculated and it is shown that they are well approximated by known analytical expressions. Those approximations allow explicitly filtering and predicting the process under study. Numerical calculations were performed on the Lomonosov-2 supercomputer at Moscow State University.","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 2","pages":"S202 - S208"},"PeriodicalIF":0.4,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148695105","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}

引用次数: 0

Modeling the Content Fragments of the Common Digital Space of Scientific Knowledge 科学知识公共数字空间的内容片段建模

IF 0.4

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2026-08-10 DOI: 10.3103/S0005105526700299

S. A. Vlasova, N. E. Kalenov, A. N. Sotnikov

{"title":"Modeling the Content Fragments of the Common Digital Space of Scientific Knowledge","authors":"S. A. Vlasova, N. E. Kalenov, A. N. Sotnikov","doi":"10.3103/S0005105526700299","DOIUrl":"10.3103/S0005105526700299","url":null,"abstract":"This article reflects the results of novel research on the formation of the Common Digital Space of Scientific Knowledge (CDSSK). This work has been carried out since 2019 in a number of academic organizations, including the Interdepartmental Supercomputer Center of the Russian Academy of Sciences (now the Department of Supercomputer Systems and Parallel Computing at the National Research Center “Kurchatov Institute”). As part of these studies, the structure of the CDSSK ontology, a language for its description, and a number of unified software tools have been developed to ensure the formation of the ontology of individual subspaces and the input of various types and kinds of object attributes and named relationships into the CDSSK. Currently, the formation of CDSSK content is being modeled using the example of a universal and a number of thematic subspaces. The results of this modeling are presented below. The attributes and relationships of the Administrative Units class objects belonging to the Geography subspace, the Organizations and Their Subdivisions class, and the Classification Systems class belonging to the universal subspace are presented. The ability to navigate through the loaded real resources is demonstrated.","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 2","pages":"S145 - S150"},"PeriodicalIF":0.4,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148695106","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}

引用次数: 0

Scientific Publications and the Embedding Space of Knowledge 科学出版物与知识的嵌入空间

IF 0.4

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2026-08-10 DOI: 10.3103/S0005105526700408

A. Kh. Marinosyan, S. G. Grigoriev

{"title":"Scientific Publications and the Embedding Space of Knowledge","authors":"A. Kh. Marinosyan, S. G. Grigoriev","doi":"10.3103/S0005105526700408","DOIUrl":"10.3103/S0005105526700408","url":null,"abstract":"The article examines current challenges in scientometrics arising from the surge in publication activity and the widespread adoption of generative artificial intelligence. The existing scientometric toolkit for analyzing research activity is reviewed and categorized into quantitative metrics and science mapping methods (citation network analysis, academic genealogy, semantic analysis, etc.). An attempt is made to overcome the limitations of traditional citation analysis, such as “semantic blindness” and vulnerability to manipulation. As a potential solution, a conceptual model is proposed where the unit of analysis shifts from the publication as a whole to an individual “key statement.” This approach involves recording not only the statement’s content but also its type, area of relevance, and its logical relationship with other statements (confirmation, refutation, clarification, generalization, etc.). Within this framework, principles for calculating modified scientometric metrics are introduced. The proposed model was tested on a corpus of 728 articles from the Russian journal Informatika i Obrazovanie (Informatics and Education) (2016–2025). An analysis conducted using large language models revealed that retrospective extraction of statements faces significant hurdles due to established cultures of scientific communication. Consequently, the study highlights the advantages of having authors formulate key statements themselves as a distinct type of metadata. In conclusion, the paper outlines development paths for the concept of an “embedding space of knowledge”, which could eventually complement existing approaches to analyzing the evolution of scientific ideas and theories.","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 2","pages":"S231 - S240"},"PeriodicalIF":0.4,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148695114","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}

引用次数: 0

Artificial Intelligence Methods for Solving an Integral Equation with a Grünwald–Letnikov Fractional Integral 求解<s:1> nwald - letnikov分数阶积分方程的人工智能方法

IF 0.4

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2026-08-10 DOI: 10.3103/S000510552670041X

T. D. Nguyen, T. Yu. Gorskaya

引用次数: 0

Modeling and Calculation Method for Rod Structures Strengthened under Load 荷载作用下杆结构加固建模与计算方法

IF 0.4

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2026-08-10 DOI: 10.3103/S0005105526700421

M. N. Serazutdinov, M. N. Ubaydulloev

{"title":"Modeling and Calculation Method for Rod Structures Strengthened under Load","authors":"M. N. Serazutdinov, M. N. Ubaydulloev","doi":"10.3103/S0005105526700421","DOIUrl":"10.3103/S0005105526700421","url":null,"abstract":"Mathematical models and a variational method are presented for calculating 3D rod structures strengthened under load. These models and the calculation method offer broader capabilities compared to existing ones. Their application makes it possible to carry out calculations for rod systems strengthened by section enlargement of rods, modifying the design model, and altering the deformed state. Complex rod structures with various cross-sectional shapes are examined. The calculations are based on the hypotheses of Timoshenko’s beam theory. For thin-walled rods, the provisions of thin-walled rod theory are additionally used, taking shear deformations into account. It is assumed that the material of a rod element follows a bilinear hardening material model. The stress-strain state (SSS) of the strengthened structure is calculated in stages. At the initial stage, displacements and stresses in the structural elements under the initial loads are determined. At the second stage, the magnitudes of erection forces and stresses arising when strengthening elements are attached to the main structural elements are determined. At the final stage, the strengthened structure is calculated for the effects of additional loads applied after strengthening. Examples are presented of calculating existing structures strengthened by various methods using the proposed models and calculation method.","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 2","pages":"S245 - S251"},"PeriodicalIF":0.4,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148695108","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}

引用次数: 0

Erratum to: Types of Embeddings and Their Application in Intellectual Academic Genealogy 《嵌入类型及其在智力学术谱系中的应用》的勘误

IF 0.4

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2026-08-10 DOI: 10.3103/S0005105526080017

A. Kh. Marinosyan

引用次数: 0

Virtual Exhibition Science in the Soviet Union during the Great Patriotic War As an Element of the Common Digital Space of Scientific Knowledge 卫国战争时期苏联的虚拟展览科学作为共同科学知识数字空间的一个要素

IF 0.4

AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS Pub Date : 2026-08-10 DOI: 10.3103/S0005105526700329

A. G. Kalina, S. A. Kirillov, A. V. Lopukhona, I. N. Sobolevskaya

{"title":"Virtual Exhibition Science in the Soviet Union during the Great Patriotic War As an Element of the Common Digital Space of Scientific Knowledge","authors":"A. G. Kalina, S. A. Kirillov, A. V. Lopukhona, I. N. Sobolevskaya","doi":"10.3103/S0005105526700329","DOIUrl":"10.3103/S0005105526700329","url":null,"abstract":"An analysis of the virtual exhibition “Science of the Soviet Union during the Great Patriotic War” is presented. It was created within the framework of the digital library The Scientific Heritage of Russia (DL SHR), as an element of the developing the Common Digital Space of Scientific Knowledge. The creation and organization of this exhibition are given as a model for integrating heterogeneous digital resources for the systematic presentation of historical and scientific content. Based on a comprehensive approach, the principles of forming an interdisciplinary collection are examined. A quantitative and structural analysis of the data set is conducted, highlighting key parameters, such as the distribution of materials by language, publication year, type, and scientific discipline, using the State Rubricator of Scientific and Technical Information (SRSTI). The architecture of the exhibition’s user interface is presented. It is demonstrated how the technological solutions implemented on the DL SHR platform contribute both conserving and promoting the accessibility of scientific heritage, ensuring its accessibility to researchers, educators, and the general public.","PeriodicalId":42995,"journal":{"name":"AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS","volume":"60 2","pages":"S166 - S170"},"PeriodicalIF":0.4,"publicationDate":"2026-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148695104","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}

引用次数: 0