Search (53 results, page 1 of 3)

  • × language_ss:"e"
  • × theme_ss:"Automatisches Indexieren"
  • × year_i:[2010 TO 2020}
  1. Gábor, K.; Zargayouna, H.; Tellier, I.; Buscaldi, D.; Charnois, T.: ¬A typology of semantic relations dedicated to scientific literature analysis (2016) 0.03 
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    Language
    e
    Theme
    Semantisches Umfeld in Indexierung u. Retrieval
  2. Banerjee, K.; Johnson, M.: Improving access to archival collections with automated entity extraction (2015) 0.02 
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    Language
    e
    Source
    Code4Lib journal. Issue 29(2015), [http://journal.code4lib.org/issues/issues/issue29]
  3. Lepsky, K.; Müller, T.; Wille, J.: Metadata improvement for image information retrieval (2010) 0.01 
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  4. Simões, M. da Graça; Machado, L.M.; Souza, R.R.; Almeida, M.B.; Tavares Lopes, A.: Automatic indexing and ontologies : the consistency of research chronology and authoring in the context of Information Science (2018) 0.01 
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    Footnote
    U.d.T. 'Indexação automática e ontologias: identificação dos contributos convergentes na ciência da informação' in: Ciência da Informação 46(2017) no.1, S.152-162.
    Language
    e
    Source
    Challenges and opportunities for knowledge organization in the digital age: proceedings of the Fifteenth International ISKO Conference, 9-11 July 2018, Porto, Portugal / organized by: International Society for Knowledge Organization (ISKO), ISKO Spain and Portugal Chapter, University of Porto - Faculty of Arts and Humanities, Research Centre in Communication, Information and Digital Culture (CIC.digital) - Porto. Eds.: F. Ribeiro u. M.E. Cerveira
  5. Junger, U.: Can indexing be automated? : the example of the Deutsche Nationalbibliothek (2012) 0.01 
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  6. Junger, U.: Can indexing be automated? : the example of the Deutsche Nationalbibliothek (2014) 0.01 
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  7. 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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    Re:inventing information science in the networked society: Proceedings of the 14th International Symposium on Information Science, Zadar/Croatia, 19th-21st May 2015. Eds.: F. Pehar, C. Schloegl u. C. Wolff
  8. Munkelt, J.; Schaer, P.; Lepsky, K.: Towards an IR test collection for the German National Library (2018) 0.01 
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  9. Golub, K.; Lykke, M.; Tudhope, D.: Enhancing social tagging with automated keywords from the Dewey Decimal Classification (2014) 0.01 
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  10. 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) 0.01 
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  11. Golub, K.; Soergel, D.; Buchanan, G.; Tudhope, D.; Lykke, M.; Hiom, D.: ¬A framework for evaluating automatic indexing or classification in the context of retrieval (2016) 0.01 
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  12. Lu, K.; Mao, J.: ¬An automatic approach to weighted subject indexing : an empirical study in the biomedical domain (2015) 0.01 
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  13. Lu, K.; Mao, J.; Li, G.: Toward effective automated weighted subject indexing : a comparison of different approaches in different environments (2018) 0.01 
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  14. Golub, K.: Automatic subject indexing of text (2019) 0.01 
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  15. Chung, E.-K.; Miksa, S.; Hastings, S.K.: ¬A framework of automatic subject term assignment for text categorization : an indexing conception-based approach (2010) 0.01 
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    Abstract
    The purpose of this study is to examine whether the understandings of subject-indexing processes conducted by human indexers have a positive impact on the effectiveness of automatic subject term assignment through text categorization (TC). More specifically, human indexers' subject-indexing approaches, or conceptions, in conjunction with semantic sources were explored in the context of a typical scientific journal article dataset. Based on the premise that subject indexing approaches or conceptions with semantic sources are important for automatic subject term assignment through TC, this study proposed an indexing conception-based framework. For the purpose of this study, two research questions were explored: To what extent are semantic sources effective? To what extent are indexing conceptions effective? The experiments were conducted using a Support Vector Machine implementation in WEKA (I.H. Witten & E. Frank, [2000]). Using F-measure, the experiment results showed that cited works, source title, and title were as effective as the full text while a keyword was found more effective than the full text. In addition, the findings showed that an indexing conception-based framework was more effective than the full text. The content-oriented and the document-oriented indexing approaches especially were found more effective than the full text. Among three indexing conception-based approaches, the content-oriented approach and the document-oriented approach were more effective than the domain-oriented approach. In other words, in the context of a typical scientific journal article dataset, the objective contents and authors' intentions were more desirable for automatic subject term assignment via TC than the possible users' needs. The findings of this study support that incorporation of human indexers' indexing approaches or conception in conjunction with semantic sources has a positive impact on the effectiveness of automatic subject term assignment.
    Language
    e
  16. 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
    Language
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  17. Kajanan, S.; Bao, Y.; Datta, A.; VanderMeer, D.; Dutta, K.: Efficient automatic search query formulation using phrase-level analysis (2014) 0.01 
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  18. Souza, R.R.; Gil-Leiva, I.: Automatic indexing of scientific texts : a methodological comparison (2016) 0.01 
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    Source
    Knowledge organization for a sustainable world: challenges and perspectives for cultural, scientific, and technological sharing in a connected society : proceedings of the Fourteenth International ISKO Conference 27-29 September 2016, Rio de Janeiro, Brazil / organized by International Society for Knowledge Organization (ISKO), ISKO-Brazil, São Paulo State University ; edited by José Augusto Chaves Guimarães, Suellen Oliveira Milani, Vera Dodebei
  19. Li, X.; Zhang, A.; Li, C.; Ouyang, J.; Cai, Y.: Exploring coherent topics by topic modeling with term weighting (2018) 0.00 
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    Date
    15. 3.2019 18:55:29
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  20. Wang, S.; Koopman, R.: Embed first, then predict (2019) 0.00 
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    Date
    29. 9.2019 12:18:42
    Language
    e

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