-
Hauer, M.: Tiefenindexierung im Bibliothekskatalog : 17 Jahre intelligentCAPTURE (2019)
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- Content
- Vgl.: https://www.b-i-t-online.de/heft/2019-02-index.php.
- Source
- B.I.T.online. 22(2019) H.2, S.163-166
-
Lepsky, K.; Müller, T.; Wille, J.: Metadata improvement for image information retrieval (2010)
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-
Gábor, K.; Zargayouna, H.; Tellier, I.; Buscaldi, D.; Charnois, T.: ¬A typology of semantic relations dedicated to scientific literature analysis (2016)
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-
Busch, D.: Domänenspezifische hybride automatische Indexierung von bibliographischen Metadaten (2019)
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- Content
- Vgl.: https://www.b-i-t-online.de/heft/2019-06-index.php.
- Source
- B.I.T.online. 22(2019) H.6, S.465-469
-
Borko, H.; Bernick, M.: Automatic document classification : T.2 (1964)
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-
Borko, H.; Bernick, M.: Automatic document classification : T.1 (1963)
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-
Kutschekmanesch, S.; Lutes, B.; Moelle, K.; Thiel, U.; Tzeras, K.: Automated multilingual indexing : a synthesis of rule-based and thesaurus-based methods (1998)
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- Source
- Information und Märkte: 50. Deutscher Dokumentartag 1998, Kongreß der Deutschen Gesellschaft für Dokumentation e.V. (DGD), Rheinische Friedrich-Wilhelms-Universität Bonn, 22.-24. September 1998. Hrsg. von Marlies Ockenfeld u. Gerhard J. Mantwill
-
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)
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- Abstract
- Wir leben im 21. Jahrhundert, und vieles, was vor hundert und noch vor fünfzig Jahren als Science Fiction abgetan worden wäre, ist mittlerweile Realität. Raumsonden fliegen zum Mars, machen dort Experimente und liefern Daten zur Erde zurück. Roboter werden für Routineaufgaben eingesetzt, zum Beispiel in der Industrie oder in der Medizin. Digitalisierung, künstliche Intelligenz und automatisierte Verfahren sind kaum mehr aus unserem Alltag wegzudenken. Grundlage vieler Prozesse sind lernende Algorithmen. Die fortschreitende digitale Transformation ist global und umfasst alle Lebens- und Arbeitsbereiche: Wirtschaft, Gesellschaft und Politik. Sie eröffnet neue Möglichkeiten, von denen auch Bibliotheken profitieren. Der starke Anstieg digitaler Publikationen, die einen wichtigen und prozentual immer größer werdenden Teil des Kulturerbes darstellen, sollte für Bibliotheken Anlass sein, diese Möglichkeiten aktiv aufzugreifen und einzusetzen. Die Auswertbarkeit digitaler Inhalte, beispielsweise durch Text- and Data-Mining (TDM), und die Entwicklung technischer Verfahren, mittels derer Inhalte miteinander vernetzt und semantisch in Beziehung gesetzt werden können, bieten Raum, auch bibliothekarische Erschließungsverfahren neu zu denken. Daher beschäftigt sich die Deutsche Nationalbibliothek (DNB) seit einigen Jahren mit der Frage, wie sich die Prozesse bei der Erschließung von Medienwerken verbessern und maschinell unterstützen lassen. Sie steht dabei im regelmäßigen kollegialen Austausch mit anderen Bibliotheken, die sich ebenfalls aktiv mit dieser Fragestellung befassen, sowie mit europäischen Nationalbibliotheken, die ihrerseits Interesse an dem Thema und den Erfahrungen der DNB haben. Als Nationalbibliothek mit umfangreichen Beständen an digitalen Publikationen hat die DNB auch Expertise bei der digitalen Langzeitarchivierung aufgebaut und ist im Netzwerk ihrer Partner als kompetente Gesprächspartnerin geschätzt.
- Date
- 19. 8.2017 9:24:22
-
Biebricher, N.; Fuhr, N.; Lustig, G.; Schwantner, M.; Knorz, G.: ¬The automatic indexing system AIR/PHYS : from research to application (1988)
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- Date
- 16. 8.1998 12:51:22
- Footnote
- Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.513-517.
-
Donahue, J.; Hendricks, L.A.; Guadarrama, S.; Rohrbach, M.; Venugopalan, S.; Saenko, K.; Darrell, T.: Long-term recurrent convolutional networks for visual recognition and description (2014)
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-
Salton, G.; Araya, J.: On the use of clustered file organizations in information search and retrieval (1990)
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- Source
- Library classification and its functions. Int. Conf. on ..., 20.-21.6.1989, Edmonton, Alberta. Ed.: A. Nitecki u. T. Fell
-
Sack, H.: Hybride Künstliche Intelligenz in der automatisierten Inhaltserschließung (2021)
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- Abstract
- Effizienter (Online-)Zugang zu Bibliotheks- und Archivmaterialien erfordert eine qualitativ hinreichende inhaltliche Erschließung dieser Dokumente. Die passgenaue Verschlagwortung und Kategorisierung dieser unstrukturierten Dokumente ermöglichen einen strukturell gegliederten Zugang sowohl in der analogen als auch in der digitalen Welt. Darüber hinaus erweitert eine vollständige Transkription der Dokumente den Zugang über die Möglichkeiten der Volltextsuche. Angesichts der in jüngster Zeit erzielten spektakulären Erfolge der Künstlichen Intelligenz liegt die Schlussfolgerung nahe, dass auch das Problem der automatisierten Inhaltserschließung für Bibliotheken und Archive als mehr oder weniger gelöst anzusehen wäre. Allerdings lassen sich die oftmals nur in thematisch engen Teilbereichen erzielten Erfolge nicht immer problemlos verallgemeinern oder in einen neuen Kontext übertragen. Das Ziel der vorliegenden Darstellung liegt in der Diskussion des aktuellen Stands der Technik der automatisierten inhaltlichen Erschließung anhand ausgewählter Beispiele sowie möglicher Fortschritte und Prognosen basierend auf aktuellen Entwicklungen des maschinellen Lernens und der Künstlichen Intelligenz einschließlich deren Kritik.
-
Lepsky, K.; Vorhauer, J.: Lingo - ein open source System für die Automatische Indexierung deutschsprachiger Dokumente (2006)
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- Date
- 24. 3.2006 12:22:02
-
Bunk, T.: Deskriptoren Stoppwortlisten und kryptische Zeichen (2008)
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-
Mödden, E.: Inhaltserschließung im Zeitalter von Suchmaschinen und Volltextsuche (2018)
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- Content
- Vgl.: https://www.b-i-t-online.de/heft/2018-01-interview-moedden.pdf.
-
Cunningham, P.; Veale, T.; Conway, A.: Knowledge acquisition for concept indexing in document retrieval (1992)
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-
Pritchard-Schoch, T.: Natural language comes of age (1993)
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