AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS最新文献

In this paper, we consider some approaches to causality in epistemology and their connection with JSM method of automated research support (JSM method ARS). The JSM method ARS is able to detect various types of cause-and-effect dependencies in data using appropriate strategies. Some approaches to causality in medicine (uniqueness of a cause, multiple causes, and independent causes) and their reflection in JSM method ARS are presented. Using a research of establishing a link between negative schizophrenia and genetic parameters as a case study, it is shown the choice of an appropriate type of causality determined in JSM method ARS using strategies. In the research under consideration, two strategies of JSM method ARS were used: one with the method of simple similarity with a ban on counterexample and the one with the generalized method. The application of the first method demonstrated a low rate of explainability of the initial data array by the generated hypotheses, which does not satisfy the criterion of abductive acceptance of hypotheses. The application of the generalized method improved the explanatory rates, which may indicate a more successful representation of the relationship between genetic parameters and the disease studied in the research. This representation is associated with the ternary similarity relation underlying the generalized method: “cause—set of brakes (blockers) of the cause—effect.”

This paper addresses the problem of the objective assessment of information processing effectiveness based on digital twins. A method was designed to establish correspondence between structural and functional models in event-driven process methodology notation and a symbolic description that can be transformed to a programming language based on a group of rules is described. Based on a given structural and functional model, examples of symbolic description and the R programming language are given. The results of the information processing research using this statistical analysis technique are presented.

Abstract—The issues of building socio-cyber-physical systems and the use of digital counterparts in them are considered. A mechanism for continuous dynamic rebuilding of digital twins for various stages of the life cycle of systems is proposed. This mechanism provides the transformation of the models that digital twins are based on, which can be performed not only during the transition between different stages of the system life cycle but also within a single stage. As an example, the transformation of the human competence model is shown.

The processes of extracting and comparing mathematical methods from scientific publications using different approaches—large language models, machine learning based classification method, and probabilistic topic modelling—are discussed. The superiority of the model obtained with probabilistic topic modelling when studying each article separately and of the large language model when studying whole projects is revealed, as well as the significant superiority of combining the results of these two approaches.

This paper presents the methodology of the quantitative study of the dynamics of changes in the thematic structure of collections and vocabulary of terms that were aimed at selecting documents into thematic collections, creating thematic (classification and subject) profiles of these collections in different chronological periods and a comparative analysis of these profiles. The profiles are treated as descriptive sets, with TF-IDF used as the keyword weight. The methodology is tested in two collections, “Robotics and Robotic Systems” and “Intelligent Systems, Artificial Intelligence, and Machine Learning.”

This article considers software for automated image analysis that must work from the operator’s mobile device, automatically perform high-quality image analysis for clarity, offer recommendations based on the output results, save images on the device in a report, determine the network signal level, send a report to the server, and delete it. The applied specificity of the problem being solved consists in the analysis of images that captured data from control panels, consoles, lifting sensors, and transport vehicles involved in logistics processes on the territory of a multimodal transport and logistics center. Automation is provided by the operation of a mathematical model based on the Laplace variation for analyzing image clarity with sufficient detail and microcontrast of captured objects. All of the steps in development are described, and the rationale for choosing the mathematical apparatus and technology stack is given. This approach ensures the validity of the process and the research results.

This article considers the frame as a model of representing knowledge in intelligent systems that allows knowledge hierarchy to be organized. It is shown that intelligent systems with knowledge bases can solve tasks that are both unknown and known to them in conditions of uncertainty and incomplete information. Frames extend the potential of intellectual systems and, like object-oriented systems, provide a mechanism of such organization, representing entities as structured objects with named cells and values associated with them. The issues of frame semantics, decision making, and peculiarities of functioning of intelligent systems using frames are discussed.

The article considers the repeatability of ChatGPT results over time intervals as a machine translator from Russian into English, using a method for the quantitative assessment of the weighting of each category describing the trajectory of translations of the same phrases over time. The experiment is described on a corpus of 50 phrases in Russian, translated into English weekly for 12 weeks. As a result, an array of 600 phrase pairs has been obtained each containing a phrase in Russian and its English translation. For each of the 50 source phrases and the corresponding 12 translations, a series of 12 annotations has been generated, including headings for classifying translation errors or a note about their absence. All of the translation series have been divided into six categories depending on the series trajectory: quality deterioration over the interval, quality improvement, quality variation, change in the set of errors without translation quality dynamics, translation change without translation quality dynamics, and translation series without change.

Object detection is actively used to search for the objects of predefined classes in an image. Object detection is actively used to search for objects of predetermined classes in an image. The model developed by the author finds arbitrary entities in a picture, not limited to predetermined classes, and generates text describing these entities.

An algebraic point of view on the description of abstract data types is applied to JSM reasoning: names of sorts and types of algebraic operations are presented together with equations that can determine their meaning. These equations form a convergent system of term rewriting. The Wolfram language is used for the equation definitions. The algebraic specification could be used both to create an ontology and to program an implementation of plausible reasoning.