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  • × type_ss:"el"
  • × theme_ss:"Automatisches Indexieren"
  1. Junger, U.; Schwens, U.: ¬Die inhaltliche Erschließung des schriftlichen kulturellen Erbes auf dem Weg in die Zukunft : Automatische Vergabe von Schlagwörtern in der Deutschen Nationalbibliothek (2017) 0.02 
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    Date
    19. 8.2017 9:24:22
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  2. Gross, D.: Maschinelle Bilderkennung mit Big Data und Deep Learning (2017) 0.00 
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  3. Peters, G.: Verschlagwortung und automatische Verfahren in der G+J Dokumentation (2003) 0.00 
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  4. Wiesenmüller, H.: Maschinelle Indexierung am Beispiel der DNB : Analyse und Entwicklungmöglichkeiten (2018) 0.00 
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  5. Mongin, L.; Fu, Y.Y.; Mostafa, J.: Open Archives data Service prototype and automated subject indexing using D-Lib archive content as a testbed (2003) 0.00 
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    Source
    D-Lib magazine. 9(2003) no.12, x S
  6. Pielmeier, S.; Voß, V.; Carstensen, H.; Kahl, B.: Online-Workshop "Computerunterstützte Inhaltserschließung" 2020 (2021) 0.00 
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  7. Wiesenmüller, H.: DNB-Sacherschließung : Neues für die Reihen A und B (2019) 0.00 
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  8. Beckmann, R.; Hinrichs, I.; Janßen, M.; Milmeister, G.; Schäuble, P.: ¬Der Digitale Assistent DA-3 : Eine Plattform für die Inhaltserschließung (2019) 0.00 
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  9. Zimmermann, H.H.: Möglichkeiten einer computergestützen Sacherschließung (2003) 0.00 
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  10. Strobel, S.: Englischsprachige Erweiterung des TIB / AV-Portals : Ein GND/DBpedia-Mapping zur Gewinnung eines englischen Begriffssystems (2014) 0.00 
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  11. Junger, U.: Can indexing be automated? : the example of the Deutsche Nationalbibliothek (2012) 0.00 
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  12. Gábor, K.; Zargayouna, H.; Tellier, I.; Buscaldi, D.; Charnois, T.: ¬A typology of semantic relations dedicated to scientific literature analysis (2016) 0.00 
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  13. Mödden, E.; Dreger, A.; Hommes, K.P.; Mohammadianbisheh, N.; Mölck, L.; Pinna, L.; Sitte-Zöllner, D.: ¬Der Weg zur Gründung der AG Erschließung ÖB-DNB und die Entwicklung eines maschinellen Verfahrens zur Verschlagwortung der Kinder- und Jugendliteratur mit GND-Vokabular (2020) 0.00 
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  14. Schöneberg, U.; Gödert, W.: Erschließung mathematischer Publikationen mittels linguistischer Verfahren (2012) 0.00 
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  15. Wolfram Language erkennt Bilder (2015) 0.00 
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  16. Mielke, B.: Wider einige gängige Ansichten zur juristischen Informationserschließung (2002) 0.00 
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  17. Franke-Maier, M.; Beck, C.; Kasprzik, A.; Maas, J.F.; Pielmeier, S.; Wiesenmüller, H: ¬Ein Feuerwerk an Algorithmen und der Startschuss zur Bildung eines Kompetenznetzwerks für maschinelle Erschließung : Bericht zur Fachtagung Netzwerk maschinelle Erschließung an der Deutschen Nationalbibliothek am 10. und 11. Oktober 2019 (2020) 0.00 
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  18. Tavakolizadeh-Ravari, M.: Analysis of the long term dynamics in thesaurus developments and its consequences (2017) 0.00 
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    Abstract
    Die Arbeit analysiert die dynamische Entwicklung und den Gebrauch von Thesaurusbegriffen. Zusätzlich konzentriert sie sich auf die Faktoren, die die Zahl von Indexbegriffen pro Dokument oder Zeitschrift beeinflussen. Als Untersuchungsobjekt dienten der MeSH und die entsprechende Datenbank "MEDLINE". Die wichtigsten Konsequenzen sind: 1. Der MeSH-Thesaurus hat sich durch drei unterschiedliche Phasen jeweils logarithmisch entwickelt. Solch einen Thesaurus sollte folgenden Gleichung folgen: "T = 3.076,6 Ln (d) - 22.695 + 0,0039d" (T = Begriffe, Ln = natürlicher Logarithmus und d = Dokumente). Um solch einen Thesaurus zu konstruieren, muss man demnach etwa 1.600 Dokumente von unterschiedlichen Themen des Bereiches des Thesaurus haben. Die dynamische Entwicklung von Thesauri wie MeSH erfordert die Einführung eines neuen Begriffs pro Indexierung von 256 neuen Dokumenten. 2. Die Verteilung der Thesaurusbegriffe erbrachte drei Kategorien: starke, normale und selten verwendete Headings. Die letzte Gruppe ist in einer Testphase, während in der ersten und zweiten Kategorie die neu hinzukommenden Deskriptoren zu einem Thesauruswachstum führen. 3. Es gibt ein logarithmisches Verhältnis zwischen der Zahl von Index-Begriffen pro Aufsatz und dessen Seitenzahl für die Artikeln zwischen einer und einundzwanzig Seiten. 4. Zeitschriftenaufsätze, die in MEDLINE mit Abstracts erscheinen erhalten fast zwei Deskriptoren mehr. 5. Die Findablity der nicht-englisch sprachigen Dokumente in MEDLINE ist geringer als die englische Dokumente. 6. Aufsätze der Zeitschriften mit einem Impact Factor 0 bis fünfzehn erhalten nicht mehr Indexbegriffe als die der anderen von MEDINE erfassten Zeitschriften. 7. In einem Indexierungssystem haben unterschiedliche Zeitschriften mehr oder weniger Gewicht in ihrem Findability. Die Verteilung der Indexbegriffe pro Seite hat gezeigt, dass es bei MEDLINE drei Kategorien der Publikationen gibt. Außerdem gibt es wenige stark bevorzugten Zeitschriften."
  19. Kaufmann, E.: ¬Das Indexieren von natürlichsprachlichen Dokumenten und die inverse Seitenhäufigkeit (2001) 0.00 
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  20. Vinyals, O.; Toshev, A.; Bengio, S.; Erhan, D.: Show and tell : a neural image caption generator (2014) 0.00 
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  • d 19
  • e 6

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