Search (41 results, page 1 of 3)

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  • × theme_ss:"Automatisches Indexieren"
  1. Fuhr, N.; Niewelt, B.: ¬Ein Retrievaltest mit automatisch indexierten Dokumenten (1984) 0.09
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    Date
    20.10.2000 12:22:23
  2. Kutschekmanesch, S.; Lutes, B.; Moelle, K.; Thiel, U.; Tzeras, K.: Automated multilingual indexing : a synthesis of rule-based and thesaurus-based methods (1998) 0.06
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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
  3. Martins, A.L.; Souza, R.R.; Ribeiro de Mello, H.: ¬The use of noun phrases in information retrieval : proposing a mechanism for automatic classification (2014) 0.03
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    Abstract
    This paper presents a research on syntactic structures known as noun phrases (NP) being applied to increase the effectiveness and efficiency of the mechanisms for the document's classification. Our hypothesis is the fact that the NP can be used instead of single words as a semantic aggregator to reduce the number of words that will be used for the classification system without losing its semantic coverage, increasing its efficiency. The experiment divided the documents classification process in three phases: a) NP preprocessing b) system training; and c) classification experiments. In the first step, a corpus of digitalized texts was submitted to a natural language processing platform1 in which the part-of-speech tagging was done, and them PERL scripts pertaining to the PALAVRAS package were used to extract the Noun Phrases. The preprocessing also involved the tasks of a) removing NP low meaning pre-modifiers, as quantifiers; b) identification of synonyms and corresponding substitution for common hyperonyms; and c) stemming of the relevant words contained in the NP, for similitude checking with other NPs. The first tests with the resulting documents have demonstrated its effectiveness. We have compared the structural similarity of the documents before and after the whole pre-processing steps of phase one. The texts maintained the consistency with the original and have kept the readability. The second phase involves submitting the modified documents to a SVM algorithm to identify clusters and classify the documents. The classification rules are to be established using a machine learning approach. Finally, tests will be conducted to check the effectiveness of the whole process.
    Source
    Knowledge organization in the 21st century: between historical patterns and future prospects. Proceedings of the Thirteenth International ISKO Conference 19-22 May 2014, Kraków, Poland. Ed.: Wieslaw Babik
  4. Greiner-Petter, A.; Schubotz, M.; Cohl, H.S.; Gipp, B.: Semantic preserving bijective mappings for expressions involving special functions between computer algebra systems and document preparation systems (2019) 0.02
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    Date
    20. 1.2015 18:30:22
  5. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.02
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
  6. Hlava, M.M.K.: Automatic indexing : comparing rule-based and statistics-based indexing systems (2005) 0.02
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    Source
    Information outlook. 9(2005) no.8, S.22-23
  7. Thirion, B.; Leroy, J.P.; Baudic, F.; Douyère, M.; Piot, J.; Darmoni, S.J.: SDI selecting, decribing, and indexing : did you mean automatically? (2001) 0.02
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  8. Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986) 0.02
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    Date
    14. 6.2015 22:12:44
  9. Hauer, M.: Automatische Indexierung (2000) 0.02
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    Source
    Wissen in Aktion: Wege des Knowledge Managements. 22. Online-Tagung der DGI, Frankfurt am Main, 2.-4.5.2000. Proceedings. Hrsg.: R. Schmidt
  10. Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986) 0.02
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    Date
    14. 6.2015 22:12:56
  11. Hauer, M.: Tiefenindexierung im Bibliothekskatalog : 17 Jahre intelligentCAPTURE (2019) 0.02
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    Source
    B.I.T.online. 22(2019) H.2, S.163-166
  12. Wiesenmüller, H.: DNB-Sacherschließung : Neues für die Reihen A und B (2019) 0.02
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    Abstract
    "Alle paar Jahre wird die Bibliothekscommunity mit Veränderungen in der inhaltlichen Erschließung durch die Deutsche Nationalbibliothek konfrontiert. Sicher werden sich viele noch an die Einschnitte des Jahres 2014 für die Reihe A erinnern: Seither werden u.a. Ratgeber, Sprachwörterbücher, Reiseführer und Kochbücher nicht mehr mit Schlagwörtern erschlossen (vgl. das DNB-Konzept von 2014). Das Jahr 2017 brachte die Einführung der maschinellen Indexierung für die Reihen B und H bei gleichzeitigem Verlust der DDC-Tiefenerschließung (vgl. DNB-Informationen von 2017). Virulent war seither die Frage, was mit der Reihe A passieren würde. Seit wenigen Tagen kann man dies nun auf der Website der DNB nachlesen. (Nebenbei: Es ist zu befürchten, dass viele Links in diesem Blog-Beitrag in absehbarer Zeit nicht mehr funktionieren werden, da ein Relaunch der DNB-Website angekündigt ist. Wie beim letzten Mal wird es vermutlich auch diesmal keine Weiterleitungen von den alten auf die neuen URLs geben.)"
    Source
    https://www.basiswissen-rda.de/dnb-sacherschliessung-reihen-a-und-b/
  13. Thönssen, B.: Automatische Indexierung und Schnittstellen zu Thesauri (1988) 0.02
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  14. Biebricher, P.; Fuhr, N.; Niewelt, B.: ¬Der AIR-Retrievaltest (1986) 0.02
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  15. Biebricher, N.; Fuhr, N.; Lustig, G.; Schwantner, M.; Knorz, G.: ¬The automatic indexing system AIR/PHYS : from research to application (1988) 0.02
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    Date
    16. 8.1998 12:51:22
  16. Tsareva, P.V.: Algoritmy dlya raspoznavaniya pozitivnykh i negativnykh vkhozdenii deskriptorov v tekst i protsedura avtomaticheskoi klassifikatsii tekstov (1999) 0.02
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    Date
    1. 4.2002 10:22:41
  17. Stankovic, R. et al.: Indexing of textual databases based on lexical resources : a case study for Serbian (2016) 0.02
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    Date
    1. 2.2016 18:25:22
  18. Tsujii, J.-I.: Automatic acquisition of semantic collocation from corpora (1995) 0.01
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    Date
    31. 7.1996 9:22:19
  19. 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
  20. 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

Years

Languages

  • e 22
  • d 18
  • ru 1
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