Analysis of the Distribution of Key Terms in Scientific Articles

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Svetlana Aleksandrovna Vlasova
Nikolay Evgenievich Kalenov
Irina Nikolaevna Sobolevskaya

Abstract

One of the Common Digital Space of Scientific Knowledge (CDSSK) main components are the subject ontologies of individual thematic subspaces, which include the basic concepts related to this scientific area. The constructing subject ontologies task at the initial phase requires the array of key terms formation in a given scientific are with the subsequent establishment of links between them. A similar task is in the encyclopedias formation in terms of the articles (slots) list generating that determines their content. One of the sources for the formation of the key terms array can be the metadata of articles published in the leading scientific journals. Namely, the author's key terms ("keywords" in the terminology of the journals editors) quoted by the article. To make a conclusion about the possibility of using this approach to the subject ontologies formation, it is necessary to conduct the author's key terms array preanalysis, both in terms of real correspondence to the main areas of research in this science branch and in terms of the distribution of the certain terms occurrence frequency. This article presents the results of the occurrence frequency analysis of the author's key terms in Russian and English, carried out on the software processing basis of several thousand articles from leading Russian journals in mathematics, computer science and physics, reflected in the MathNet database. An assessment was made of the distribution of key terms correspondence (as phrases) and individual words to the Bradford's law, and the key terms cores within the thematic direction were identified.

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References

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