Search (680 results, page 1 of 34)

  • × year_i:[2010 TO 2020}
  1. Verwer, K.: Freiheit und Verantwortung bei Hans Jonas (2011) 0.09
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    Content
    Vgl.: http%3A%2F%2Fcreativechoice.org%2Fdoc%2FHansJonas.pdf&usg=AOvVaw1TM3teaYKgABL5H9yoIifA&opi=89978449.
  2. Koch, C.: Consciousness : confessions of a romantic reductionist (2012) 0.08
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  3. Roth, G.; Strüber, N.: Wie das Gehirn die Seele macht (2018) 0.07
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  4. Kleineberg, M.: Context analysis and context indexing : formal pragmatics in knowledge organization (2014) 0.07
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    Source
    http://www.google.de/url?sa=t&rct=j&q=&esrc=s&source=web&cd=5&ved=0CDQQFjAE&url=http%3A%2F%2Fdigbib.ubka.uni-karlsruhe.de%2Fvolltexte%2Fdocuments%2F3131107&ei=HzFWVYvGMsiNsgGTyoFI&usg=AFQjCNE2FHUeR9oQTQlNC4TPedv4Mo3DaQ&sig2=Rlzpr7a3BLZZkqZCXXN_IA&bvm=bv.93564037,d.bGg&cad=rja
  5. Erpenbeck, J.; Sauter, W.: Stoppt die Kompetenzkatastrophe! : Wege in eine neue Bildungswelt (2019) 0.07
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    Classification
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  6. Unzicker, A.: Vom Urknall zum Durchknall (2010) 0.06
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  7. Liessmann, K.P.: Geisterstunde : die Praxis der Unbildung ; eine Streitschrift (2014) 0.06
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    Classification
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  8. Costandi, M.: Neuroplasticity (2016) 0.06
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    Classification
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  9. Roth, G.; Strüber, N.: Wie das Gehirn die Seele macht (2014) 0.06
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    Classification
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  10. Sweller, J.; Ayres, P.; Kalyuga, S.: Cognitive load theory (2011) 0.05
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    Classification
    CX 1000
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  11. Cognitive load theory (2010) 0.05
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    Classification
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  12. Lippmann, W.: ¬Die öffentliche Meinung : wie sie entsteht und manipuliert wird (2018) 0.05
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    Classification
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  13. O'Connor, C.; Weatherall, J.O.: ¬The misinformation age : how false ideas spread (2019) 0.05
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    Classification
    MF 1000
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    MF 1000
  14. Blanco, E.; Cankaya, H.C.; Moldovan, D.: Composition of semantic relations : model and applications (2010) 0.05
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    Content
    Vgl. unter: http://www.hlt.utdallas.edu/~eduardo/papers/csr_model_and_applications.pdf. Vgl. für den Proceedingsband: http://www.aclweb.org/anthology/C/C10/C10-1000.pdf.
  15. Gödert, W.; Lepsky, K.: Informationelle Kompetenz : ein humanistischer Entwurf (2019) 0.05
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    Footnote
    Rez. in: Philosophisch-ethische Rezensionen vom 09.11.2019 (Jürgen Czogalla), Unter: https://philosophisch-ethische-rezensionen.de/rezension/Goedert1.html. In: B.I.T. online 23(2020) H.3, S.345-347 (W. Sühl-Strohmenger) [Unter: https%3A%2F%2Fwww.b-i-t-online.de%2Fheft%2F2020-03-rezensionen.pdf&usg=AOvVaw0iY3f_zNcvEjeZ6inHVnOK]. In: Open Password Nr. 805 vom 14.08.2020 (H.-C. Hobohm) [Unter: https://www.password-online.de/?mailpoet_router&endpoint=view_in_browser&action=view&data=WzE0MywiOGI3NjZkZmNkZjQ1IiwwLDAsMTMxLDFd].
  16. Lindpointner, R.: ¬Die Einführung der Dewey-Dezimalklassifikation (DDC) in der Oberösterreichischen Landesbibliothek (OÖLB) (2010) 0.05
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    Abstract
    Der Grund für die Einführung der DDC war die Umstellung auf Freihand durch den damals bevorstehenden Umbau und Ausbau der Bibliothek. Durch die Errichtung von 3 Tiefgeschoßen war es möglich, das gesamte oberirdische Magazin für das Publikum zu öffnen, wodurch die Publikumsflächen von vorher weniger als 200 m**2 auf nun 2200 m**2 ausgeweitet werden konnten. Zur Ausgangssituation: Wir hatten damals eine Freihand-Bibliothek im Umfang von einigen tausend Nachschlagewerken im Lesesaal, die wir einige Jahre zuvor - nach einem Umbau des Lesesaals - grob nach der 3-stelligen DDC aufgestellt hatten. Aber im Grunde genommen war das Thema Freihand für uns vollkommenes Neuland.
  17. Losee, R.M.: ¬The effect of assigning a metadata or indexing term on document ordering (2013) 0.05
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    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.11, S.2191-2200
  18. Floridi, L.: Information: a very short introduction (2010) 0.04
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    Classification
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  19. Hayek, F.A.: ¬Der Weg zur Knechtschaft (2019) 0.04
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  20. Wolfangel, E.: ¬Die Grenzen der künstlichen Intelligenz (2016) 0.04
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    Content
    "Wie lernen Maschinen überhaupt? Eine zentrale Unterscheidung betrifft die Art des Lernens: Algorithmen können überwacht oder unüberwacht lernen. Ersteres wird unter anderem für Klassifikationsaufgaben genutzt: Ist beispielsweise ein Mensch auf einem Foto oder nicht? Grundlage dafür sind Trainingsdaten, anhand derer der Algorithmus auf Vorgabe eines Menschen lernt, was das richtige Ergebnis ist - auf diesen 1000 Bildern ist ein Mensch, auf diesen 1000 nicht. Hat das System für alle eventuell vorkommenden Fälle genügend Trainingsdaten, so die Idee, lernt es daraus selbst, bislang unbekannte Bilder zu klassifizieren. Alphago lernte beispielsweise unter anderem anhand von Millionen menschlicher Go-Spielzüge.
    Neuronale Netze lernen aus Erfahrungen Angesichts immer größerer Computer und wachsender Masse an Trainingsdaten gewinnen bei der Bilderkennung so genannte neuronale Netze immer mehr an Bedeutung. "Sie sind heute die leistungsfähigsten Mustererkennungsverfahren", sagt Hamprecht. Dabei wird die Funktionsweise des menschlichen Gehirns lose nachgeahmt: Die Netze bestehen aus mehreren Lagen mit einer festzulegenden Anzahl an Neuronen, deren Verbindungen sich verstärken oder abschwächen abhängig von den "Erfahrungen", die sie machen. Solche Erfahrungen sind beispielsweise die Trainingsdaten aus dem überwachten Lernen und das Feedback, ob zu einem Trainingsdatum die richtige oder falsche Vorhersage gemacht wurde. Dank der vielen Übungsdaten lassen sich heute sehr viel größere und tiefere Netze trainieren als noch vor einigen Jahren. Während früher ein berühmter Computer-Vision-Datensatz aus 256 Bildern und sein Nachfolger aus 1000 Bildern bestand, gibt es heute Datensätze mit einer Million gelabelter Bilder - also solche, auf denen Menschen markiert haben, was darauf zu sehen ist. Aber die Netze haben auch entscheidende Haken: "Man kann bei neuronalen Netzen schwer nachvollziehen, wie sie zu einer Entscheidung kamen", sagt Hamprecht. Zudem beruhe der Entwurf neuronaler Netze auf einer großen Willkür: Bei der Entscheidung, wie viele Lagen mit wie vielen Neuronen genutzt werden sollten, beruhe vieles auf Bauchgefühl oder auf Ausprobieren. Die Entwickler testen verschiedene Varianten und schauen, wann das beste Ergebnis entsteht. Erklären können sie ihre Entscheidung nicht. "Dieses Rumprobieren gefällt mir nicht", sagt Hamprecht, "ich gehe den Dingen lieber auf den Grund.""

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