AUTOMATIC DOCUMENTATION AND MATHEMATICAL LINGUISTICS最新文献

The ranking of scientific conferences plays a key role in the academic world, determining the significance and prestige of each event. The main results of ranking from the point of view of personalities are as follows: determining the quality and influence of the scientific conference; a guide for selecting a conference; encouragement to conduct quality research; formation of a scientific community; and improvement of the visibility and influence of the conference for the scientific community. This paper provides an overview of currently existing conference catalogs and conference ranking systems, both automatic ones and with the participation of expert councils. It is noted that the purpose of creating a national ranking system is to promote and popularize domestic conferences and journals. From a review of currently existing conference catalogs and conference ranking systems, the following criteria for ranking conferences can be formulated: indicators of publication activity, based on the results of the analysis of published conference materials; credibility of the speakers and the organizing committee of the conference; number of presentations and the ratio of the number of presentations to the number of conference participants; time for reviewing applications submitted to the conference; ratio of submitted and accepted applications; and retrospective and geographical parameters.

It is essential to aggregate scientific information for a comprehensive analysis of geological objects. This paper explores the potential and possibilities of semantic search to select thematically similar publications in the geological domain. Various language models are examined in the context of identifying similarities and differences in texts describing mineral deposits. After additional training, a significant improvement in search results from language models is demonstrated. Two web services are presented, based on a method for calculating the semantic similarity between texts and providing a quantitative assessment of their similarity.

To analyze heat fluxes, observational data for 1979–2018 were used for the North Atlantic. The spatiotemporal variability of the total heat flux was modeled using stochastic diffusion. The coefficients of the stochastic differential equation were estimated by using nonparametric statistics. Previously, the existence and uniqueness of a solution in the strong sense of the stochastic differential equation generated by the constructed diffusion process was proven when Kolmogorov’s conditions were met. In this work, the coefficients of the equation were approximated using trigonometric polynomials whose amplitudes and phases depended on the flow values. Using a given series of 40 years in length from 1979 to 2018, spatial maps and time curves were constructed. The results are shown for 1999 and 2018, and their comparative analysis is also carried out. Numerical calculations were performed on the Lomonosov-2 supercomputer at Lomonosov Moscow State University.

The problem of the presentation of the scientific results of academic institute in a digital environment is considered. A new look at the knowledge space of a scientific institute constitutes a natural stage in the development of WEB technologies. The data structure inherent in previous studies allows the organization, searching, and navigation of them using a knowledge graph, like a version of the semantic library LibMeta. The knowledge graph gives a more complete and high-quality idea of the knowledge space, often removing the cognitive load in the perception of complex structures and data connections.

The video editing process involves numerous labor-intensive operations for sorting and preparing footages, requiring significant time investment. This article describes the development of a software solution that uses machine learning technology to automate these processes. The primary focus is on creating a system capable of classifying and sorting media files according to the screenplay text, thereby increasing the efficiency of material preparation for editing. The system includes modules for speech recognition, audio and video classification, and algorithms for determining screenplay compliance. Testing showed that the proposed system correctly classifies media files in most cases, significantly reducing rough-cut editing time.

The enrichment of educational texts with semantic content (in particular, adding hyperlinks to the pages of a service that displays detailed information about concepts in the text) helps increase efficiency in students’ assimilation of the material. Existing methods of semantic markup of educational texts do not take into account the structural features of such documents, and this leads to an excessive recognition of concepts. This article describes the development of the method of automatic annotation of mathematical concepts in educational and mathematical texts by adding functionality to account for the structure of an educational document. The main purpose of this method is to process educational materials of the distance education course Technology for Solving Planimetric Problems. Following a single template when creating course pages allows you to apply an analysis of webpage markup and keywords that are used by the course creators. The main task in this process is to determine the type of table cell containing text fragments of educational materials. In accordance with the recommendations of the course creators, definitions should be highlighted in the cells that contain the task statement, as well as in the blocks where the input data of the task is indicated. The type of table cells is determined by analyzing their attributes and searching for keywords in their contents. This limitation of recognizable text fragments will improve the student’s perception of the course pages and improve the quality of their learning.

The problem of high and increasing cost of video game development is considered, and to solve it is proposed to apply procedural content generation, which will reduce development costs. The work is a part of a large-scale research on automatic prototyping of video games and is devoted to the processing of game scenarios, i.e. natural language texts. It is proposed to extract the necessary entities from the scripts and pass them to further steps of the algorithm, which will generate game resources based on the textual descriptions. There are several publications devoted to game text processing, in which several different structures for storing the extracted information are proposed. In this paper we propose a universal format that is suitable for processing the text of any video game and allows to create a corpus of texts for use in further research and automatic generation of game prototypes.

An approach to automatically recognizing the movement of people at a pedestrian crossing is presented in this article. This approach includes two main procedures, for each of which commands are given in the C# programming language using the EMGU computer vision library. In the first procedure, pedestrian detection is performed using the combination of a directional gradient histogram and support vector methods. The second procedure allows you to read frames from a video sequence and process them. This approach allows for the detection of the movements of people at a pedestrian crossing without using specialized neural networks. At the same time, the method proposed in this article had sufficient reliability in terms of human movement recognition, which indicates its applicability to real conditions.

An analysis of the speed and efficiency of data transfer using the WebSocket and REST API protocols was carried out. To compare the speed of processing stream objects and identify a more reliable technology for the development of APIs, expansions of basic functions in the Taylor and Fourier series were used. It was found that the REST API is a faster and more accessible resource for the transmission information data in a bitwise transformation, and the scalability of this protocol prevails in the number of processed units, which allows expanding the number of tests performed.

This paper proposes software mechanisms intended to enhance video production for the authors of artistic video materials. We propose a mechanism for creating animated three-dimensional shooting plans (storyboards) with the use of augmented reality to position and animate actors’ movements. To overcome the limitations of the iOS operating system related to access to sensors, we developed a mechanism for separately capturing audio and video streams from device sensors for recording and subsequent synchronization using timestamps for saving to device memory. Computer vision technologies are used to ensure compliance with the rules of compositional construction and image quality analysis. This paper also presents mechanisms for working with the script, including text-processing algorithms to display subtitles on the screen and speech recognition algorithms to compare actors’ speech recognition of actors with the text of the script.