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Expert, Journal, and Automatic Classification of Full Texts and Annotations of Scientific Articles

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Automatic Documentation and Mathematical Linguistics Aims and scope

Abstract—

In this article we consider a fundamentally new information-theoretic approach to the classification of scientific texts based on compression algorithms. An analysis using the example of the comparative classification of full-text documents from arXiv.org and short annotations from Scopus showed that the accuracy of the proposed method is 87–92% and, in general, is not inferior to the existing ones. These conclusions were confirmed by an expert assessment.

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ACKNOWLEDGMENTS

For the expert assessment and comments, the authors are grateful to:

Vyacheslav Nikolaevich Glinskikh, Doctor of Physical and Mathematical Sciences, Corresponding Member of the Russian Academy of Sciences, Head of the Laboratory of Multiscale Geophysics;

Dmitry Vasilyevich Metelkin, Doctor of Geological and Mineralogical Sciences, Associate Professor, Chief Researcher of the Laboratory of Geodynamics and Paleomagnetism, Chief Researcher of the Laboratory of Geodynamics and Paleomagnetism of the Central and Eastern Arctic, Faculty of Geoelogy and Geophysics, Novosibirsk State University;

Nikolay Valerianovich Sennikov, Doctor of Geological and Mineralogical Sciences, Professor, Head of the Laboratory of Paleontology and Stratigraphy of the Paleozoic, Head of the Department of Historical Geology and Paleontology, Faculty of Geoelogy and Geophysics, Novosibirsk State University;

Tatyana Mikhailovna Parfenova, Candidate of Geological and Mineralogical Sciences, Deputy Director for Research, Senior Researcher, Laboratory of Oil and Gas Geochemistry;

Irina Viktorovna Filimonova, Doctor of Economics, Professor and Head, Center for the Economics of Subsoil Use of Oil and Gas, Trofimuk Institute of Petroleum-Gas Geology and Geophysics, Siberian Branch, Russian Academy of Sciences, Head, Department of Political Economy, Faculty of Economics, Novosibirsk State University.

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Authors and Affiliations

  1. State Public Scientific Technological Library, Siberian Branch, Russian Academy of Sciences, Novosibirsk, Russia

    I. V. Selivanova, D. V. Kosyakov & A. E. Guskov

  2. Novosibirsk State University, Novosibirsk, Russia

    D. A. Dubovitskii

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  1. I. V. Selivanova
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  2. D. V. Kosyakov
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  3. D. A. Dubovitskii
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  4. A. E. Guskov
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Correspondence to I. V. Selivanova, D. V. Kosyakov, D. A. Dubovitskii or A. E. Guskov.

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Selivanova, I.V., Kosyakov, D.V., Dubovitskii, D.A. et al. Expert, Journal, and Automatic Classification of Full Texts and Annotations of Scientific Articles. Autom. Doc. Math. Linguist. 55, 178–189 (2021). https://doi.org/10.3103/S0005105521040075

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