Novosibirsk State University Journal of Information Technologies
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All Issues >> Contents: Volume 15, Issue No 1 (2017)

On the Approach to the Classification of Thesis Abstracts on Themes
Yu.V. Leonova, A. M. Fedotov, O. A. Fedotova

Institute of Computational Technologies SB RAS
Novosibirsk State University
State Public Scientific Technological Library SB RAS

UDC code: 004.9

Abstract
The method of thematic classification of thesis abstracts is considered in the work. For this purpose, a specially constructed measure of the proximity of documents is used, taking into account the specifics of the subject area. As scales for the definition of a measure, it is suggested to take the characteristics of the structural attributes of the description of the author's abstracts (scientific novelty, provisions to be defended, etc.). The values of the weight coefficients in the formula for computing the proximity measure are determined by the assumed a posteriori reliability of the data of the corresponding scale.

Key Words
classification of thesis abstracts, weight coefficients, measure of proximity, subject area, model of facet classification, classification algorithm

How to cite:
Leonova Yu. V., Fedotov A. M., Fedotova O. A. On the Approach to the Classification of Thesis Abstracts on Themes // Vestnik NSU Series: Information Technologies. - 2017. - Volume 15, Issue No 1. - P. 47-58. - ISSN 1818-7900. (in Russian).

Full Text in Russian

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References
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Publication information
Main title Vestnik NSU Series: Information Technologies, Volume 15, Issue No 1 (2017).
Parallel title: Novosibirsk State University Journal of Information Technologies Volume 15, Issue No 1 (2017).

Key title: Vestnik Novosibirskogo gosudarstvennogo universiteta. Seriâ: Informacionnye tehnologii
Abbreviated key title: Vestn. Novosib. Gos. Univ., Ser.: Inf. Tehnol.
Variant title: Vestnik NGU. Seriâ: Informacionnye tehnologii

Year of Publication: 2017
ISSN: 1818-7900 (Print), ISSN 2410-0420 (Online)
Publisher: Novosibirsk State University Press
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