Search (43 results, page 2 of 3)

  • × theme_ss:"Automatisches Indexieren"
  1. Stankovic, R. et al.: Indexing of textual databases based on lexical resources : a case study for Serbian (2016) 0.01
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    Date
    1. 2.2016 18:25:22
  2. Villaespesa, E.; Crider, S.: ¬A critical comparison analysis between human and machine-generated tags for the Metropolitan Museum of Art's collection (2021) 0.01
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    Abstract
    Purpose Based on the highlights of The Metropolitan Museum of Art's collection, the purpose of this paper is to examine the similarities and differences between the subject keywords tags assigned by the museum and those produced by three computer vision systems. Design/methodology/approach This paper uses computer vision tools to generate the data and the Getty Research Institute's Art and Architecture Thesaurus (AAT) to compare the subject keyword tags. Findings This paper finds that there are clear opportunities to use computer vision technologies to automatically generate tags that expand the terms used by the museum. This brings a new perspective to the collection that is different from the traditional art historical one. However, the study also surfaces challenges about the accuracy and lack of context within the computer vision results. Practical implications This finding has important implications on how these machine-generated tags complement the current taxonomies and vocabularies inputted in the collection database. In consequence, the museum needs to consider the selection process for choosing which computer vision system to apply to their collection. Furthermore, they also need to think critically about the kind of tags they wish to use, such as colors, materials or objects. Originality/value The study results add to the rapidly evolving field of computer vision within the art information context and provide recommendations of aspects to consider before selecting and implementing these technologies.
  3. Tsujii, J.-I.: Automatic acquisition of semantic collocation from corpora (1995) 0.01
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    Date
    31. 7.1996 9:22:19
  4. Riloff, E.: ¬An empirical study of automated dictionary construction for information extraction in three domains (1996) 0.01
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    Date
    6. 3.1997 16:22:15
  5. Lepsky, K.; Vorhauer, J.: Lingo - ein open source System für die Automatische Indexierung deutschsprachiger Dokumente (2006) 0.01
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    Date
    24. 3.2006 12:22:02
  6. Probst, M.; Mittelbach, J.: Maschinelle Indexierung in der Sacherschließung wissenschaftlicher Bibliotheken (2006) 0.01
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    Date
    22. 3.2008 12:35:19
  7. Glaesener, L.: Automatisches Indexieren einer informationswissenschaftlichen Datenbank mit Mehrwortgruppen (2012) 0.01
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    Date
    11. 9.2012 19:43:22
  8. Bordoni, L.; Pazienza, M.T.: Documents automatic indexing in an environmental domain (1997) 0.01
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    Source
    International forum on information and documentation. 22(1997) no.1, S.17-28
  9. Wolfekuhler, M.R.; Punch, W.F.: Finding salient features for personal Web pages categories (1997) 0.01
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    Date
    1. 8.1996 22:08:06
  10. Renz, M.: Automatische Inhaltserschließung im Zeichen von Wissensmanagement (2001) 0.01
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    Date
    22. 3.2001 13:14:48
  11. Newman, D.J.; Block, S.: Probabilistic topic decomposition of an eighteenth-century American newspaper (2006) 0.01
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    Date
    22. 7.2006 17:32:00
  12. Kasprzik, A.: Voraussetzungen und Anwendungspotentiale einer präzisen Sacherschließung aus Sicht der Wissenschaft (2018) 0.01
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    Abstract
    Große Aufmerksamkeit richtet sich im Moment auf das Potential von automatisierten Methoden in der Sacherschließung und deren Interaktionsmöglichkeiten mit intellektuellen Methoden. In diesem Kontext befasst sich der vorliegende Beitrag mit den folgenden Fragen: Was sind die Anforderungen an bibliothekarische Metadaten aus Sicht der Wissenschaft? Was wird gebraucht, um den Informationsbedarf der Fachcommunities zu bedienen? Und was bedeutet das entsprechend für die Automatisierung der Metadatenerstellung und -pflege? Dieser Beitrag fasst die von der Autorin eingenommene Position in einem Impulsvortrag und der Podiumsdiskussion beim Workshop der FAG "Erschließung und Informationsvermittlung" des GBV zusammen. Der Workshop fand im Rahmen der 22. Verbundkonferenz des GBV statt.
  13. Franke-Maier, M.: Anforderungen an die Qualität der Inhaltserschließung im Spannungsfeld von intellektuell und automatisch erzeugten Metadaten (2018) 0.01
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    Abstract
    Spätestens seit dem Deutschen Bibliothekartag 2018 hat sich die Diskussion zu den automatischen Verfahren der Inhaltserschließung der Deutschen Nationalbibliothek von einer politisch geführten Diskussion in eine Qualitätsdiskussion verwandelt. Der folgende Beitrag beschäftigt sich mit Fragen der Qualität von Inhaltserschließung in digitalen Zeiten, wo heterogene Erzeugnisse unterschiedlicher Verfahren aufeinandertreffen und versucht, wichtige Anforderungen an Qualität zu definieren. Dieser Tagungsbeitrag fasst die vom Autor als Impulse vorgetragenen Ideen beim Workshop der FAG "Erschließung und Informationsvermittlung" des GBV am 29. August 2018 in Kiel zusammen. Der Workshop fand im Rahmen der 22. Verbundkonferenz des GBV statt.
  14. Ward, M.L.: ¬The future of the human indexer (1996) 0.00
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    Date
    9. 2.1997 18:44:22
  15. Lorenz, S.: Konzeption und prototypische Realisierung einer begriffsbasierten Texterschließung (2006) 0.00
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    Date
    22. 3.2015 9:17:30
  16. Busch, D.: Domänenspezifische hybride automatische Indexierung von bibliographischen Metadaten (2019) 0.00
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    Source
    B.I.T.online. 22(2019) H.6, S.465-469
  17. Rasmussen, E.M.: Indexing and retrieval for the Web (2002) 0.00
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    Abstract
    Techniques for automated indexing and information retrieval (IR) have been developed, tested, and refined over the past 40 years, and are well documented (see, for example, Agosti & Smeaton, 1996; BaezaYates & Ribeiro-Neto, 1999a; Frakes & Baeza-Yates, 1992; Korfhage, 1997; Salton, 1989; Witten, Moffat, & Bell, 1999). With the introduction of the Web, and the capability to index and retrieve via search engines, these techniques have been extended to a new environment. They have been adopted, altered, and in some Gases extended to include new methods. "In short, search engines are indispensable for searching the Web, they employ a variety of relatively advanced IR techniques, and there are some peculiar aspects of search engines that make searching the Web different than more conventional information retrieval" (Gordon & Pathak, 1999, p. 145). The environment for information retrieval an the World Wide Web differs from that of "conventional" information retrieval in a number of fundamental ways. The collection is very large and changes continuously, with pages being added, deleted, and altered. Wide variability between the size, structure, focus, quality, and usefulness of documents makes Web documents much more heterogeneous than a typical electronic document collection. The wide variety of document types includes images, video, audio, and scripts, as well as many different document languages. Duplication of documents and sites is common. Documents are interconnected through networks of hyperlinks. Because of the size and dynamic nature of the Web, preprocessing all documents requires considerable resources and is often not feasible, certainly not an the frequent basis required to ensure currency. Query length is usually much shorter than in other environments-only a few words-and user behavior differs from that in other environments. These differences make the Web a novel environment for information retrieval (Baeza-Yates & Ribeiro-Neto, 1999b; Bharat & Henzinger, 1998; Huang, 2000).
  18. Plaunt, C.; Norgard, B.A.: ¬An association-based method for automatic indexing with a controlled vocabulary (1998) 0.00
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    Date
    11. 9.2000 19:53:22
  19. Milstead, J.L.: Thesauri in a full-text world (1998) 0.00
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    Date
    22. 9.1997 19:16:05
  20. 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) 0.00
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    Date
    19. 8.2017 9:24:22

Years

Languages

  • e 25
  • d 16
  • m 1
  • ru 1
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Types

  • a 38
  • el 3
  • m 2
  • x 2
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Classifications