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        Automatisierte Inhaltserschließung an der Bibliothek des Max-Planck-Instituts für Mathematik in den Naturwissenschaften

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        Author(s)
        Weers, Beatrice Simon cc
        Language
        German
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        Abstract
        This bachelor thesis deals with the topic of automated content indexing at the library of the Max Planck Institute for Mathematics in Science in Leipzig. The aim is to determine how well the library's specially developed program for automated content indexing works in comparison to intellectual indexing. To this end, some theoretical principles were examined and other current projects in Germany were presented. A study in which 97 publications were provided with notations by both the program and three test persons resulted in a 70 percent agreement between the program and at least one of the test persons. In addition, possibilities for improving the program were identified.
        URI
        https://library.oapen.org/handle/20.500.12657/110805
        Keywords
        Automatic indexing; Max Planck Institute for Mathematics in the Science (Leipzig); Special libraries (LCSH); Notation classification; HTWK Faculty of Computer Science and Media; German National Library (Deutsche Nationalbibliothek); ZBW - Leibniz Information Centre for Economics; Data collection experiment; Library science; Computer Science (LCSH)
        DOI
        10.33968/9783966270786-00
        ISBN
        9783966270786, 9783966270786, 9783966270793, 9783966270809
        Publisher
        HTWK Leipzig - OA-Hochschulverlag
        Publisher website
        https://oa-hochschulverlag.htwk-leipzig.de/mainnavigation/
        Publication date and place
        Leipzig, 2025
        Classification
        Bibliographic and subject control
        Pages
        76
        Rights
        https://creativecommons.org/licenses/by/4.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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