Abstract: Methods of the semantic documents parsing in digital control system of scientific collections, including electronic journals, offered. The methods of processing documents containing mathematical formulas and methods for the conversion of documents from the OpenXML-format in ТеХ-format considered. The search algorithm for the mathematical formulas in the collections of documents stored in OpenXML-format designed. The algorithm is implemented as online-service on platform science.tatarstan.

Abstract: The number of scientific journals published in the world is very large. In this regard, it is necessary to create software tools that will allow analyzing thematic links of journals. The algorithm presented in this paper uses graphs of co-authorship for analyzing the thematic proximity of journals. It is insensitive to the language of the journal and can find similar journals in different languages. This task is difficult for algorithms based on the analysis of full-text information. Approbation of the algorithm was carried out in the scientometric system IAS ISTINA. Using a special interface, a user can select one interesting journal. Then the system will automatically generate a selection of journals that may be of interest to the user. In the future, the developed algorithm can be adapted to search for similar conferences, collections of publications and research projects. The use of such tools will increase the publication activity of young employees, increase the citation of articles and quoting between journals. In addition, the results of the algorithm for determining thematic proximity between journals, collections, conferences and research projects can be used to build rules in the ontology models for access control systems.

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Starting from spring 2022 a national system for evaluating the effectiveness of scientific research and development is being created using the database of leading Russian journals Russian Science Citation Index (RSCI). The article represents some results of the analysis of the RSCI normalized rating published in December 2022. Using the journal citation graph constructed from the data Math-Net.Ru on the example of thematic group OECD 101.Mathematics we show that in the case of a large number of self-citations of the journals, a relationship between the normalized rating and the number of references is found, and the relationship with self-citation is somewhat stronger than without self-citation. Analysis of the distribution of the journals by thematic groups shows that using a single attribute, such as the OECD, as a criterion does not allow forming a group as a community of journals with a single strongly connected component in the citation graph. We conclude that the research methods of journal citation graphs are a good basis for a comparative analysis of the characteristics of journals and their ranking, which means they can be used as tools for further development and improvement of journal ratings.

Abstract: During the last decades scientometric techniques have been used for research activity stimulation. Number of published articles and number of their citation counts are among the most important scientometric parameters. In an automated environment, when the publications metadata is gathered from various sources, correct linking of original papers with their translations into different languages is extremely important. In the paper we show that the known text similarity measures are inefficient in the context of article linkage problem. We propose a method for semi-automatic article linkage using statistical data on authors publication activities only. This approach may be used for linking articles without training for the language of translation. The method was evaluated on real-world collection of publications metadata of ISTINA information system.

Abstract:

According to the portal Math-Net.Ru a graph of journal citation is constructed. To increase the reliability of the model, the citation time interval was chosen from 2010 to 2021, when the distribution of citation articles stabilized at the level of 3500-4500 citations per year. The structure of link aging is studied and it is shown that their half-life is equal to 8 years. Therefore, the publication date of the cited articles was limited to 2002. For the constructed citation graph, the main properties, such as a small diameter and a high density, are obtained, indicating a high level of scientific communication in the Math-Net.Ru. The absence of the “Matthew effect” as a pronounced advantage in quoting established journals in relation to less well-known ones is shown. Adequacy of the journal citation graph Math-Net.Ru as a model of scientific communication confirmed by comparing the ranking of journals in the citation graph with their SCIENCE INDEX rating in eLIBRARY.RU. A direct moderate relationship between the two rankings is shown. A number of meaningful conclusions are drawn from the analysis of the citation graph.

Abstract: The article presents the events that took place last year in the world of Russian scientific publications. There is a slow slide towards paid access of some academic journals turned in open access in 2018. The European Union has announced plan "S" for the mass transition of scientific journals to open access. New models of the scientific publication are introducing. Reporting on publications requested by the Ministry of education and science in 2019 does not take into account the size of the readership of the article. Neither the Ministry of education and science, nor the Higher Attestation Commission (HAC) does not encourage publication in the public domain. In Russian Science Citation Index began the fight against widespread fraudulent trade in references to the article, but the HAC is not interested in this activity. A proliferation of contradictory the term "self-plagiarism" has spread. This label is widely stigmatized authors and journals for repeated publications.

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Translated plagiarism has widely spread in a scientific world and posed a serious problem due to the challenges in its automatic detection. However, in the last five years some progress has been observed in this area. The authors of this paper, as well as foreign research team from several universities independently of each other proposed an approach to detect plagiarism based on citation analysis with search of initial source for analyzed suspected paper with the same or similar references. Developed methods of detection of illegal use of borrowed text successfully passed several tests. The report shows the results that we have obtained in the last four years.

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