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  • × theme_ss:"Automatisches Indexieren"
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  1. 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
  2. Krutulis, J.D.; Jacob, E.K.: ¬A theoretical model for the study of emergent structure in adaptive information networks (1995) 0.01
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    Source
    Connectedness: information, systems, people, organizations. Proceedings of CAIS/ACSI 95, the proceedings of the 23rd Annual Conference of the Canadian Association for Information Science. Ed. by Hope A. Olson and Denis B. Ward
  3. Siebenkäs, A.; Markscheffel, B.: Conception of a workflow for the semi-automatic construction of a thesaurus for the German printing industry (2015) 0.01
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  4. Wiesenmüller, H.: Maschinelle Indexierung am Beispiel der DNB : Analyse und Entwicklungmöglichkeiten (2018) 0.01
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    Abstract
    Der Beitrag untersucht die Ergebnisse des bei der Deutschen Nationalbibliothek (DNB) eingesetzten Verfahrens zur automatischen Vergabe von Schlagwörtern. Seit 2017 kommt dieses auch bei Printausgaben der Reihen B und H der Deutschen Nationalbibliografie zum Einsatz. Die zentralen Problembereiche werden dargestellt und an Beispielen illustriert - beispielsweise dass nicht alle im Inhaltsverzeichnis vorkommenden Wörter tatsächlich thematische Aspekte ausdrücken und dass die Software sehr häufig Körperschaften und andere "Named entities" nicht erkennt. Die maschinell generierten Ergebnisse sind derzeit sehr unbefriedigend. Es werden Überlegungen für mögliche Verbesserungen und sinnvolle Strategien angestellt.
  5. Hodges, P.R.: Keyword in title indexes : effectiveness of retrieval in computer searches (1983) 0.01
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    Date
    14. 3.1996 13:22:21
  6. 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
  7. 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
  8. Renz, M.: Automatische Inhaltserschließung im Zeichen von Wissensmanagement (2001) 0.01
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    Date
    22. 3.2001 13:14:48
  9. 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
  10. 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.
  11. 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.
  12. Cui, H.; Boufford, D.; Selden, P.: Semantic annotation of biosystematics literature without training examples (2010) 0.01
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    Abstract
    This article presents an unsupervised algorithm for semantic annotation of morphological descriptions of whole organisms. The algorithm is able to annotate plain text descriptions with high accuracy at the clause level by exploiting the corpus itself. In other words, the algorithm does not need lexicons, syntactic parsers, training examples, or annotation templates. The evaluation on two real-life description collections in botany and paleontology shows that the algorithm has the following desirable features: (a) reduces/eliminates manual labor required to compile dictionaries and prepare source documents; (b) improves annotation coverage: the algorithm annotates what appears in documents and is not limited by predefined and often incomplete templates; (c) learns clean and reusable concepts: the algorithm learns organ names and character states that can be used to construct reusable domain lexicons, as opposed to collection-dependent patterns whose applicability is often limited to a particular collection; (d) insensitive to collection size; and (e) runs in linear time with respect to the number of clauses to be annotated.
  13. Kiros, R.; Salakhutdinov, R.; Zemel, R.S.: Unifying visual-semantic embeddings with multimodal neural language models (2014) 0.01
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    Abstract
    Inspired by recent advances in multimodal learning and machine translation, we introduce an encoder-decoder pipeline that learns (a): a multimodal joint embedding space with images and text and (b): a novel language model for decoding distributed representations from our space. Our pipeline effectively unifies joint image-text embedding models with multimodal neural language models. We introduce the structure-content neural language model that disentangles the structure of a sentence to its content, conditioned on representations produced by the encoder. The encoder allows one to rank images and sentences while the decoder can generate novel descriptions from scratch. Using LSTM to encode sentences, we match the state-of-the-art performance on Flickr8K and Flickr30K without using object detections. We also set new best results when using the 19-layer Oxford convolutional network. Furthermore we show that with linear encoders, the learned embedding space captures multimodal regularities in terms of vector space arithmetic e.g. *image of a blue car* - "blue" + "red" is near images of red cars. Sample captions generated for 800 images are made available for comparison.
  14. Mielke, B.: Wider einige gängige Ansichten zur juristischen Informationserschließung (2002) 0.01
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  15. Pielmeier, S.; Voß, V.; Carstensen, H.; Kahl, B.: Online-Workshop "Computerunterstützte Inhaltserschließung" 2020 (2021) 0.01
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  16. Ward, M.L.: ¬The future of the human indexer (1996) 0.01
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    Date
    9. 2.1997 18:44:22
  17. Busch, D.: Domänenspezifische hybride automatische Indexierung von bibliographischen Metadaten (2019) 0.01
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    Source
    B.I.T.online. 22(2019) H.6, S.465-469
  18. Plaunt, C.; Norgard, B.A.: ¬An association-based method for automatic indexing with a controlled vocabulary (1998) 0.01
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    Date
    11. 9.2000 19:53:22
  19. Milstead, J.L.: Thesauri in a full-text world (1998) 0.01
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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) 0.01
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    Date
    19. 8.2017 9:24:22

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