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Abstract: An approach is proposed for organizing expert evaluation of a scientific document submitted to a mathematical journal. Domain restriction is associated with the use of the Mathematical Sciences Classification System – MSC. A recommendation system is presented that allows you to create a list of possible experts for conducting scientific peer-reviewing on a mathematical article. The recommender system uses the MSC codes presented by the author of the article on the MSC2020 classifiers. If the codes MSC2000 or MSC2010 are indicated in the article, they are automatically converted to codes MSC2020. For each expert, the system supports a personal profile that contains a set of codes MSC2020, supplemented by numerical characteristics – weights calculated for each code in accordance with the system of accounting for competencies, preferences or refusals to participate in the review procedure. This set is automatically edited if the expert is included in the list of possible reviewers – the weights of several codes increase or decrease, as well as new codes are added. The recommendation system is implemented as an integrated tool (plug-in) of the Open Journal Systems (OJS) platform. The developed method has been tested in the information system of the Lobachevskii Journal of Mathematics (https://ljm.kpfu.ru).

Abstract: Features of use of information systems in the process of electronic scientific publications issues investigated. From the standpoint of automation editorial processes, we compared these systems. Algorithms for automatic validation of mathematical texts style introduced into the information system of the electronic scientific journal. The method of automating the process of peer review, including the selection of reviewers, e-mail notifications and control the timing of reviewing proposed. Automation technology a number of editorial processes of electronic scientific journal, operates on a platform Open Journal Systems is presented.

Abstract: A number of problems related to the construction of the metadata factory of the digital mathematical library Lobachevskii-DML have been solved. By metadata factory we mean a system of interconnected software tools aimed at creating, processing, storing and managing metadata of digital library objects and allowing integrating created electronic collections into aggregating digital scientific libraries. In order to select the optimal such software tools from existing ones and their modernization:we discussed the features of the presentation of the metadata of documents of various electronic collections related both to the formats used and to changes in the composition and completeness of the set of metadata throughout the entire publication of the corresponding scientific journal;we presented and characterized software tools for managing scientific content and methods for organizing automated integration of repositories of mathematical documents with other information systems;we discussed such an important function of the digital library metadata factory as the normalization of metadata in accordance with the formats of other aggregating libraries.As a result of the development of the metadata factory of the digital mathematical library Lobachevskii-DML, we proposed a system of services for the automated generation of metadata for electronic mathematical collections; we have developed an xml metadata presentation language based on the Journal Archiving and Interchange Tag Suite (NISO JATS); we have created software tools for normalizing metadata of electronic collections of scientific documents in formats developed by international organizations – aggregators of resources in mathematics and Computer Science; we have developed an algorithm for converting metadata to oai_dc format and generating the archive structure for import into DSpace digital storage; we have proposed and implemented methods for integrating electronic mathematical collections of Kazan University into domestic and foreign digital mathematical libraries.

Abstract:

The modern information space contains a lot of data, but they are often poorly structured, difficult to find and not always correct. This creates additional difficulties during researches, so digital spaces of scientific knowledge are currently being formed, in particular, based on knowledge graphs.

To ensure the quality of information, such graphs are often filled with data manually, which is time-consuming. Therefore, the creation of a tool that provides the ability to automate process of filling a graph with data, as well as ensures data quality, will simplify and speed up the process of forming digital spaces of scientific knowledge.

Methods for automating the filling of the graph with data are proposed, including parallel control of their integrity. Based on the proposed methods, a software module has been developed, the mechanisms of its functioning and its architecture are described.

Abstract:

An algorithm for automatic extraction of bibliographic data from a one-dimensional array of publications (in particular, the issues of the scientific journal) and the formation of metadata blocks for export to international information-analytical system. The methods of integration management platform electronic scientific journals (Open Journal Systems) and Science Citation Index.

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The results on the creation of methods for managing mathematical knowledge in the context of digital mathematical libraries are presented. The software tools developed on the basis of these methods are part of the OntoMath digital ecosystem, within which they interact. A brief description of the architecture of the OntoMath ecosystem is given, the levels of subject ontologies and external ontologies are highlighted, as well as the level of software tools and services. Semantic services are separated into a separate category. This term denotes software tools, in the functionality of which queries to subject ontologies are used to ensure the management of knowledge objects. General descriptions of developed subject ontologies are given: educational mathematical ontology OntoMath^Edu and ontology of professional mathematics OntoMath^PRO. The development of educational ontology is reflected in the direction of including educational prerequisite links between classes. Among the software tools of the digital ecosystem, search services for mathematical electronic collections, a service for semantic annotation of mathematical documents, tools for semantic marking of educational mathematical documents, as well as a system for automatically generating testing tests in mathematical educational disciplines are highlighted. As part of the OntoMath digital ecosystem, special-purpose recommender systems are being developed. The current version of the ecosystem includes a recommender system for generating a list of related articles based on the OntoMath^PRO ontology, a recommender system for appointing experts to support the scientific review process, and recommender systems for selecting subject classifiers UDC and Mathematics Subject Classification codes for mathematical documents. The results are also presented in the direction of creating a digital library metadata factory, which includes services and tools for extracting, refining, replenishing and normalizing the metadata of electronic mathematical collections. Note that the OntoMath ecosystem is being developed as the technological basis for the Lobachevskii Digital Mathematical Library.

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Abstract:

We investigated the current models of the publication and dissemination of scientific knowledge. We describe the modern information management system of scientific publications and services that determine their functionality.

We discuss the concept of the digital infrastructure of the electronic scientific journal. Under this infrastructure, we understand the complex that combines management software platform of electronic journal and a number of specialized information systems. The software platform realizes the basic operating log management processes. Information systems provide the operation of additional services, taking into account the specifics of the journal subject area.

We present an approach to the organization of the digital infrastructure of the scientific journal based on an open platform Open Journal Systems (OJS). We provide software services that extend the functionality of this platform and considering specificity of the subject area of scientific journals. We have created software modules for automating of electronic scientific journal workflow. These modules are an extension of OJS.

We present a system of services for the automated processing of collections of scientific documents. These services provide verification of document compliance to the accepted rules of formation of collections and their conversion to the established formats; structural analysis of documents and extraction of metadata, as well as their integration into the scientific information space. The system allows to automatically performing a set of operations that cannot be realized for acceptable time with the traditional manual processing of electronic content. It is designed for the large collections of scientific documents.

Algorithms style validation of texts at the article registration stage in the information system of electronic scientific journal, the selection of reviewers, alert and control the timing of reviewing were automated. Information gathering algorithm with dedicated news lines of scientific journals, further analysis and distribution of news by categories and degrees of importance were developed. The algorithm automatically extract bibliographic data from a homogeneous array of publications (in particular, the issues of the scientific journal) and the formation of metadata blocks for export to international information and analytical system were created. Methods integration of OJS platform and international databases of science citation were developed.

We present methods of processing documents containing mathematical formulas: in the collections of documents that contain mathematical formulas, algorithm for the search formulas is developed; basic ideas, approaches and results already obtained by the mathematical knowledge management based on ontology are presented; a method of constructing recommender systems based on mathematical knowledge ontologies described. The method of primary processing automated of scientific article using TеX-notation developed.

The new direction of researches of scientific communications in the environment of Web 2.0 – altmetrics – is considered. We have analyzed the content of the notion «altmetrics», we conducted a comparison of traditional (bibliometric and scientometric) and alternative indicators. We describe the use of world experience informetric services on scientific journals sites. We discussed options for implementing these approaches to create an electronic scientific journal management platform. 

Abstract:

Methods for creating digital mathematical collections that include unstructured sets of documents are presented. These sets contain materials from scientific conferences, as well as articles from the archives of mathematical journals of the "pre-digital" period.

Using the software tools of the metadata factory of the digital mathematical library Lobachevskii DML, a mandatory set of metadata for digital collection documents was formed. To refine and replenish the metadata sets, knowledge extraction methods from Wikidata were used.

To search Wikidata for information about digital collection documents and their authors, a system of SPARQL queries has been developed. A set of Wikidata entities is defined, which determine the features of the search, as well as the subsequent filtering of the results.

Methods for clarifying and supplementing the bibliographic references given in the articles are proposed. When forming the metadata of documents of retrocollections, a search was made in Wikidata for information about the years of life of the authors of articles, as well as URLs of web pages with information about articles and their authors. The results of the formation of several new digital collections of the Lobachevskii-DML digital library are presented.

Abstract: In the present paper we consider applications of Semantic Web technologies to electronic scientific collections. We describe approaches based on XML, RDF and other technologies of Semantic Web to managing electronic collections, and, in particular, to generating metadata, organization of data storage, and data search. These approaches have been used in the project ``Scientific Electronic Library: eLibrary.ru'' and in the electronic l «Lobachevskii Journal of Mathematics» (http://ljm.ksu.ru).

Abstract: This article analyzes the development trends of processing Big Data tools and multi-format data storage and analysis. This analysis was carried out as part of our program of basic research of the Department of Mathematical Sciences, Russian Academy of Sciences “Algebraic and Combinatorial Methods of Mathematical Cybernetics and information systems of the new generation", as well as RFBR grant number 14-07-00783 “Way to store and process a large volume of scientific and reference data modern hardware platforms”.

Abstract:

The solutions of the main problems associated with the formation of digital mathematical collections from documents published in the pre-digital period are presented – such collections are designated in the work as retro collections. Algorithms for creating a meta description of retro collections based on the analysis of the structure of mathematical documents and the use of software tools for extracting metadata are given. The description of retro-collections formed using the developed algorithms and included in the metadata factory of the digital mathematical library Lobachevskii-DML is given. The schemes for the formation of metadata and methods for normalizing the extracted metadata in accordance with the schemes and requirements of the integrating mathematical libraries are indicated.

Abstract: Описаны направления российских исследований и разработок в области научных электронных журналов. Приведены статистические материалы, характеризующие работу нескольких наиболее успешно функционирующих электронных журналов за все время их существования, в том числе распределение статей по тематике, и статистика запросов на материалы журналов. Сделана попытка ответа на вопрос, кто является типичным автором полностью электронных журналов.
Обсуждены вопросы сохранения целостности материалов журналов и их архивации, организации всей технологической цепочки «автор – редакция – рецензент – редакция – сайт», сохранения авторских прав, официальной регистрации журналов и некоторые другие юридические проблемы.
Сделан краткий обзор существующих в России полностью электронных научных журналов, указаны их особенности, приведена сравнительная классификация. Уделено внимание способам разметки и поисковым системам.
Представлены основные результаты по созданию и реализации технологии автоматизированной обработки и включения в соответствующие базы данных (в частности, в базу данных Научной электронной библиотеки) электронных научных журналов с учетом имеющихся стандартов и рекомендаций, достигнутые при поддержке Российского фонда фундаментальных исследований в рамках проекта 03-07-90252.

Abstract: We investigated the current models of the publication and dissemination of scientific knowledge. We also presented different approaches to the organization of the personal information space of scientist. We describe the modern information management system of scientific publications and services that determine their functionality. We have created software modules for automating of electronic scientific journal workflow. These modules are an extension of Open Journal Systems. We describe the architecture of a universal information management system of electronic scientific journals and management platform of “Russian Digital Libraries Journal”.

Abstract:

Recently, such a direction of machine learning as reinforcement learning has been actively developing. As a consequence, attempts are being made to use reinforcement learning for solving computer vision problems, in particular for solving the problem of image classification. The tasks of computer vision are currently one of the most urgent tasks of artificial intelligence.

The article proposes a method for image classification in the form of a deep neural network using reinforcement learning. The idea of ​​the developed method comes down to solving the problem of a contextual multi-armed bandit using various strategies for achieving a compromise between exploitation and research and reinforcement learning algorithms. Strategies such as -greedy, -softmax, -decay-softmax, and the UCB1 method, and reinforcement learning algorithms such as DQN, REINFORCE, and A2C are considered. The analysis of the influence of various parameters on the efficiency of the method is carried out, and options for further development of the method are proposed.

Abstract: Описаны направления исследований и разработок в области электронных библиотек – информационных систем нового класса. Указаны особенности научных электронных библиотек. Представлены основные результаты работ по методической поддержке создания и использования научных электронных библиотек, выполненных на базе Института развития информационного общества при поддержке РФФИ в рамках проектов 01-07-90444 и 04-07-90184, а также при поддержке РГНФ в рамках проекта 03-02-12008.