Abstract: В статье содержится обзор известных инструментов подготовки математических текстов, а также обсуждаются различные способы представления их в Веб: TeX/LaTeX, MathML, графические форматы. Рассмотрены основные функции и возможности данных инструментов, их достоинства и недостатки. Представлен обзор инструментов для конвертирования математических данных из формата TeX/LaTeX в MathML, из MathML в TeX/LaTeX, из формата содержательной разметки MathML в формат презентационной разметки MathML.

Abstract:

In recent years, the presentation of full-text scientific articles in HTML has become widespread. This format offers several advantages for online publication compared to the traditional PDF format, owing to its more advanced tools for structuring material, embedding multimedia content, and implementing various interactive and dynamic features. Therefore, the task of converting manuscripts from the traditionally used MS Word and LaTeX formats into a high-quality HTML version capable of realizing the advantages of this format has become relevant. This paper presents the results of applying the approach for converting scientific articles from MS Word to HTML, proposed in previous studies, to Keldysh Institute of Applied Mathematics’ preprints. The interactive capabilities of the resulting HTML versions are described.

Abstract:

This paper examines the development of the SciLibRu library of scientific subject areas, as a continuation of the semantic description of scientific works from the library LibMeta project. This library is based on a conceptual data model, the structure and semantics of which are formed based on the principles of ontological modeling. This approach ensures a strict description of the subject area, formalization of the relationships between entities, and the possibility of further automated data analysis. The goal of the study is to develop and experimentally apply methods for structuring scientific journal data in LaTeX format for their integration into the library ontology and to support semantic search.

An algorithm for translating data represented by multiple files into XML format is proposed for integration into the library ontology. A vector search module based on embedding calculation using language models is implemented. Patterns in the distribution of embeddings and factors influencing the accuracy of search results ranking are identified. Testing of the two components is conducted.

The developed method forms the basis for automatically incorporating scientific journal data into the SciLibRu knowledge graph and creating training corpora for language models limited to scientific subject areas. The obtained results contribute to the development of journal knowledge graph navigation systems, recommendation engines, and intelligent search tools for Russian-language scientific texts.