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  1. Suchenwirth, L.: Sacherschliessung in Zeiten von Corona : neue Herausforderungen und Chancen (2019) 0.24
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    Abstract
    Eine der wesentlichen Aufgaben als Fachreferent*in ist die inhaltliche Erschließung der neuerworbenen Literatur, sowie die Begutachtung und Auswahl der neu erschienenen Werke in den jeweiligen Fachgebieten hinsichtlich der Relevanz für die eigenen Sammlungen gemäß dem Sammlungsprofil der TU Wien Bibliothek. Im Zuge der Corona-Krise wurde die herkömmliche Arbeitsweise in der Sacherschließung beeinträchtigt, und es haben sich neue Herausforderungen, aber auch Möglichkeiten ergeben. Neben der fehlenden Autopsie der Literatur leidet auch die Sichtung und Erwerbung neuer Literatur unter der physischen Abwesenheit vom Arbeitsplatz bzw. der entsprechenden technischen Infrastruktur. Auch der persönliche Austausch mit den Kolleg*innen wurde deutlich erschwert. Neben den Schwierigkeiten wurden aber auch die neuen Handlungsoptionen auf beruflicher und individueller Ebene positiv gesehen. In dem Artikel werden unsere individuellen Erfahrungen an der TU Wien Bibliothek sowie Ausblicke in die Zukunft wiedergegeben.
    Footnote
    https%3A%2F%2Fjournals.univie.ac.at%2Findex.php%2Fvoebm%2Farticle%2Fdownload%2F5332%2F5271%2F&usg=AOvVaw2yQdFGHlmOwVls7ANCpTii.
  2. Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004) 0.17
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    Content
    Vgl.: http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=1&cad=rja&ved=0CEAQFjAA&url=http%3A%2F%2Fciteseerx.ist.psu.edu%2Fviewdoc%2Fdownload%3Fdoi%3D10.1.1.91.4940%26rep%3Drep1%26type%3Dpdf&ei=dOXrUMeIDYHDtQahsIGACg&usg=AFQjCNHFWVh6gNPvnOrOS9R3rkrXCNVD-A&sig2=5I2F5evRfMnsttSgFF9g7Q&bvm=bv.1357316858,d.Yms.
    Date
    8. 1.2013 10:22:32
  3. Zschunke, P.: Intelligenz nach Bauplan : "Computer sind dumm" - mit diesem Vorurteil muß man wohl in Zukunft vorsichtig sein. Neuronale Netze simulieren den Schaltplan des Gehirns. Sie sind lernfähig und fehlertolerant (1997) 0.17
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    Date
    18. 1.1997 12:15:22
  4. Li, L.; Shang, Y.; Zhang, W.: Improvement of HITS-based algorithms on Web documents 0.14
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    Content
    Vgl.: http%3A%2F%2Fdelab.csd.auth.gr%2F~dimitris%2Fcourses%2Fir_spring06%2Fpage_rank_computing%2Fp527-li.pdf. Vgl. auch: http://www2002.org/CDROM/refereed/643/.
  5. Schrodt, R.: Tiefen und Untiefen im wissenschaftlichen Sprachgebrauch (2008) 0.14
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    Content
    Vgl. auch: https://studylibde.com/doc/13053640/richard-schrodt. Vgl. auch: http%3A%2F%2Fwww.univie.ac.at%2FGermanistik%2Fschrodt%2Fvorlesung%2Fwissenschaftssprache.doc&usg=AOvVaw1lDLDR6NFf1W0-oC9mEUJf.
  6. Popper, K.R.: Three worlds : the Tanner lecture on human values. Deliverd at the University of Michigan, April 7, 1978 (1978) 0.14
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    Source
    https%3A%2F%2Ftannerlectures.utah.edu%2F_documents%2Fa-to-z%2Fp%2Fpopper80.pdf&usg=AOvVaw3f4QRTEH-OEBmoYr2J_c7H
  7. Herb, U.; Beucke, D.: ¬Die Zukunft der Impact-Messung : Social Media, Nutzung und Zitate im World Wide Web (2013) 0.14
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    Content
    Vgl. unter: https://www.leibniz-science20.de%2Fforschung%2Fprojekte%2Faltmetrics-in-verschiedenen-wissenschaftsdisziplinen%2F&ei=2jTgVaaXGcK4Udj1qdgB&usg=AFQjCNFOPdONj4RKBDf9YDJOLuz3lkGYlg&sig2=5YI3KWIGxBmk5_kv0P_8iQ.
  8. Krämer, S.: Künstliche Intelligenz : der Aufstieg des Computers zum Modellbaukasten des Geistes (1994) 0.13
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    Abstract
    Die Interpreten Künstlicher Intelligenz sind konfrontiert mit einem Paradoxon. Die praktischen Wirkungen Künstlicher Intelligenz sind minimal. Doch theoretisch betrachtet entfaltet die Künstliche Intelligenz eine ungebrochene Attraktivität und füllt die Feuilleton-Seiten ebenso zugkräftig wie die philosophischen Seminare. Die Künstliche Intelligenz - diese Schlußfolgerung drängt sich auf - wirkt weniger als eine Technik, sondern als eine Idee. Nicht ihre faktische Ingenieurleistung zählt, sondern das ihr zugrundeliegende Modell vom Geist
    Source
    Information Philosophie. 22(1994) H.2, S.16-28
  9. Vetere, G.; Lenzerini, M.: Models for semantic interoperability in service-oriented architectures (2005) 0.12
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    Content
    Vgl.: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=5386707&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D5386707.
  10. Singer, W.: Hirnentwicklung oder die Suche nach Kohärenz (1994) 0.11
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    Date
    22. 7.2000 18:43:51
    Source
    Geist - Gehirn - Künstliche Intelligenz: zeitgenössische Modelle des Denkens. Ringvorlesung an der Freien Universität. Hrsg.: S. Krämer
  11. Friederici, A.: Gehirn und Sprache : Neurobiologische Grundlagen der Sprachverarbeitung (1994) 0.11
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    Date
    22. 7.2000 18:43:38
    Source
    Geist - Gehirn - Künstliche Intelligenz: zeitgenössische Modelle des Denkens. Ringvorlesung an der Freien Universität. Hrsg.: S. Krämer
  12. ¬Der Student aus dem Computer (2023) 0.11
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    Abstract
    Kann gut zitieren, aber schlecht rechnen: Künstliche Intelligenz besteht Juraprüfung an US-Uni
    Date
    27. 1.2023 16:22:55
  13. Schneider, R.U.: Darf der Computer die Seminararbeit schreiben? (2023) 0.11
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    Abstract
    Fast alle Studenten lassen sich bei schriftlichen Arbeiten von künstlicher Intelligenz helfen. Manche halten das für Betrug, andere für die Zukunft der Bildung.
  14. Mas, S.; Marleau, Y.: Proposition of a faceted classification model to support corporate information organization and digital records management (2009) 0.11
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    Footnote
    Vgl.: http://ieeexplore.ieee.org/Xplore/login.jsp?reload=true&url=http%3A%2F%2Fieeexplore.ieee.org%2Fiel5%2F4755313%2F4755314%2F04755480.pdf%3Farnumber%3D4755480&authDecision=-203.
  15. Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019) 0.11
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    Content
    Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
  16. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.11
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    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  17. Plomin, R.; DeFries, J.C.: Erblichkeit kognitiver Stärken und Schwächen (1999) 0.11
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    Abstract
    Schätzungsweise 30.000 unserer Gene werden im Gehirn ausgeprägt, und jedes könnte mit Intelligenz zu tun haben. Herauszufinden, welche davon bestimmt Komponenten unseres Intellekts mitgestalten oder zur Intelligenz allgemein beitragen, gleicht einer Sisyphusarbeit. Sie trägt aber erste Früchte
    Date
    22. 7.2000 19:01:54
  18. Zilm, G.: "Kl ist ein glorifizierter Taschenrechner" (2023) 0.11
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    Abstract
    Künstliche Intelligenz zieht immer mehr in unseren Alltag ein. Dies macht vielen Angst. Sie fürchten, der Mensch könne die Kontrolle über Kl verlieren. Wie das verhindert werden kann, darüber macht sich das Ethik-Team am Deutschen Forschungszentrum für Künstliche Intelligenz Gedanken. Das DFKI hat mehrere Standorte, die Zentrale ist in Kaiserslautern.
    Date
    27. 1.2023 16:22:55
  19. Rötzer, F.: Psychologen für die Künstliche Intelligenz (2018) 0.10
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    Abstract
    Künstliche Intelligenz kann lernen anhand von Erfahrungen und Vorgaben. Das Problem ist aber, dass sich maschinelles Lernen zwar in eine bestimmte Richtung steuern lässt, um bestimmte Probleme zu lösen, dass aber der Programmierer mitunter nicht mehr weiß, was in dem "künstlichen Gehirn" bzw. dem neuronalen Netzwerk vor sich geht, das mit zunehmender Komplexität und Lernerfahrung für den Menschen zur Black Box wird, wo man nur sehen kann, was an Daten einfließt und was herauskommt.
    Date
    22. 1.2018 11:08:27
    Source
    https://www.heise.de/tp/features/Psychologen-fuer-die-Kuenstliche-Intelligenz-3947256.html?view=print
  20. Röscheisen, E.: Fin de such (2001) 0.09
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    Abstract
    Die klassischen Portale entwickeln sich von der Suchmaschine zum Informationsbroker weiter. Die Zukunft der Suche nach Information wird ganz im Zeichen Künstlicher Intelligenz, verteilter Agenten und Wissensmanagement stehen - verschiedene spezialisierte Anbieter liefern bereits heute einen ersten vorgeschmack

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