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  1. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.03 
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    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  2. Großjohann, K.: Gathering-, Harvesting-, Suchmaschinen (1996) 0.03 
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    Date
    7. 2.1996 22:38:41
    Pages
    22 S
  3. Lange, C.; Ion, P.; Dimou, A.; Bratsas, C.; Sperber, W.; Kohlhasel, M.; Antoniou, I.: Getting mathematics towards the Web of Data : the case of the Mathematics Subject Classification (2012) 0.02 
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    Abstract
    The Mathematics Subject Classification (MSC), maintained by the American Mathematical Society's Mathematical Reviews (MR) and FIZ Karlsruhe's Zentralblatt für Mathematik (Zbl), is a scheme for classifying publications in mathematics according to their subjects. While it is widely used, its traditional, idiosyncratic conceptualization and representation requires custom implementations of search, query and annotation support. This did not encourage people to create and explore connections of mathematics to subjects of related domains (e.g. science), and it made the scheme hard to maintain. We have reimplemented the current version of MSC2010 as a Linked Open Dataset using SKOS and our focus is concentrated on turning it into the new MSC authority. This paper explains the motivation, and details of our design considerations and how we realized them in the implementation. We present in-the-field use cases and point out how e-science applications can take advantage of the MSC LOD set. We conclude with a roadmap for bootstrapping the presence of mathematical and mathematics-based science, technology, and engineering knowledge on the Web of Data, where it has been noticeably underrepresented so far, starting from MSC/SKOS as a seed.
  4. Wätjen, H.-J.: Mensch oder Maschine? : Auswahl und Erschließung vonm Informationsressourcen im Internet (1996) 0.02 
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    Date
    2. 2.1996 15:40:22
  5. Luo, L.; Ju, J.; Li, Y.-F.; Haffari, G.; Xiong, B.; Pan, S.: ChatRule: mining logical rules with large language models for knowledge graph reasoning (2023) 0.01 
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    Date
    23.11.2023 19:07:22

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