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Hotho, A.; Bloehdorn, S.: Data Mining 2004 : Text classification by boosting weak learners based on terms and concepts (2004)
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- 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
-
Li, L.; Shang, Y.; Zhang, W.: Improvement of HITS-based algorithms on Web documents
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Suchenwirth, L.: Sacherschliessung in Zeiten von Corona : neue Herausforderungen und Chancen (2019)
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- Footnote
- https%3A%2F%2Fjournals.univie.ac.at%2Findex.php%2Fvoebm%2Farticle%2Fdownload%2F5332%2F5271%2F&usg=AOvVaw2yQdFGHlmOwVls7ANCpTii.
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Schrodt, R.: Tiefen und Untiefen im wissenschaftlichen Sprachgebrauch (2008)
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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.
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Popper, K.R.: Three worlds : the Tanner lecture on human values. Deliverd at the University of Michigan, April 7, 1978 (1978)
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Friederici, A.: Gehirn und Sprache : Neurobiologische Grundlagen der Sprachverarbeitung (1994)
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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
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Vetere, G.; Lenzerini, M.: Models for semantic interoperability in service-oriented architectures (2005)
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Singer, W.: Hirnentwicklung oder die Suche nach Kohärenz (1994)
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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
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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.
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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)
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- Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
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Noever, D.; Ciolino, M.: ¬The Turing deception (2022)
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- Source
- https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
-
Axelos, C.; Flasch, K.; Schepers, H.; Kuhlen, R.; Romberg, R.; Zimmermann, R.: Allgemeines/Besonderes (1971-2007)
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- Footnote
- DOI: 10.24894/HWPh.5033. Vgl. unter: https://www.schwabeonline.ch/schwabe-xaveropp/elibrary/start.xav#__elibrary__%2F%2F*%5B%40attr_id%3D%27verw.allgemeinesbesonderes%27%5D__1515856414979.
-
Plomin, R.; DeFries, J.C.: Erblichkeit kognitiver Stärken und Schwächen (1999)
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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
-
Siekmann, J.H.: Künstliche Intelligenz (1994)
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- Source
- Geist - Gehirn - Künstliche Intelligenz: zeitgenössische Modelle des Denkens. Ringvorlesung an der Freien Universität. Hrsg.: S. Krämer
-
Donsbach, W.: Wahrheit in den Medien : über den Sinn eines methodischen Objektivitätsbegriffes (2001)
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- Source
- Politische Meinung. 381(2001) Nr.1, S.65-74 [https%3A%2F%2Fwww.dgfe.de%2Ffileadmin%2FOrdnerRedakteure%2FSektionen%2FSek02_AEW%2FKWF%2FPublikationen_Reihe_1989-2003%2FBand_17%2FBd_17_1994_355-406_A.pdf&usg=AOvVaw2KcbRsHy5UQ9QRIUyuOLNi]
-
Malsburg, C. von der: ¬The correlation theory of brain function (1981)
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- Source
- http%3A%2F%2Fcogprints.org%2F1380%2F1%2FvdM_correlation.pdf&usg=AOvVaw0g7DvZbQPb2U7dYb49b9v_
-
Herb, U.; Beucke, D.: ¬Die Zukunft der Impact-Messung : Social Media, Nutzung und Zitate im World Wide Web (2013)
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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.
-
Rötzer, F.: Psychologen für die Künstliche Intelligenz (2018)
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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
-
Floyd, C.: Künstliche Intelligenz - Verantwortungsvolles Handeln (1994)
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- Source
- Geist - Gehirn - Künstliche Intelligenz: zeitgenössische Modelle des Denkens. Ringvorlesung an der Freien Universität. Hrsg.: S. Krämer
-
Straschill, M.: Ist der Geist im Gehirn lokalisierbar? (1994)
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- Source
- Geist - Gehirn - Künstliche Intelligenz: zeitgenössische Modelle des Denkens. Ringvorlesung an der Freien Universität. Hrsg.: S. Krämer