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  • × theme_ss:"Automatisches Indexieren"
  1. Schröther, C.: Automatische Indexierung, Kategorisierung und inhaltliche Erschließung von Textnachrichten (2003) 0.06
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    Footnote
    Magisterarbeit, Phil. Fak. der Rheinischen Friedrich-Wilhelms-Universität Bonn (Prof. Dr. W. Lenders)
  2. Böhm, A.; Seifert, C.; Schlötterer, J.; Granitzer, M.: Identifying tweets from the economic domain (2017) 0.03
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    Source
    Theorie, Semantik und Organisation von Wissen: Proceedings der 13. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) und dem 13. Internationalen Symposium der Informationswissenschaft der Higher Education Association for Information Science (HI) Potsdam (19.-20.03.2013): 'Theory, Information and Organization of Knowledge' / Proceedings der 14. Tagung der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) und Natural Language & Information Systems (NLDB) Passau (16.06.2015): 'Lexical Resources for Knowledge Organization' / Proceedings des Workshops der Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) auf der SEMANTICS Leipzig (1.09.2014): 'Knowledge Organization and Semantic Web' / Proceedings des Workshops der Polnischen und Deutschen Sektion der Internationalen Gesellschaft für Wissensorganisation (ISKO) Cottbus (29.-30.09.2011): 'Economics of Knowledge Production and Organization'. Hrsg. von W. Babik, H.P. Ohly u. K. Weber
  3. Leung, C.-H.; Kan, W.-K.: ¬A statistical learning approach to automatic indexing of controlled index terms (1997) 0.03
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  4. Goller, C.; Löning, J.; Will, T.; Wolff, W.: Automatic document classification : a thourough evaluation of various methods (2000) 0.03
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  5. Schöneberg, U.; Gödert, W.: Erschließung mathematischer Publikationen mittels linguistischer Verfahren (2012) 0.03
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    Source
    http://at.yorku.ca/c/b/f/j/99.htm
  6. Li, W.; Wong, K.-F.; Yuan, C.: Toward automatic Chinese temporal information extraction (2001) 0.02
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  7. Yang, T.-H.; Hsieh, Y.-L.; Liu, S.-H.; Chang, Y.-C.; Hsu, W.-L.: ¬A flexible template generation and matching method with applications for publication reference metadata extraction (2021) 0.02
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  8. Plaunt, C.; Norgard, B.A.: ¬An association-based method for automatic indexing with a controlled vocabulary (1998) 0.02
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    Date
    11. 9.2000 19:53:22
  9. 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) 0.02
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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
  10. Keitz, W. von: Automatic indexing and the dissemination of information (1986) 0.02
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  11. Nohr, H.: Grundlagen der automatischen Indexierung : ein Lehrbuch (2003) 0.02
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    Date
    22. 6.2009 12:46:51
    Footnote
    Rez. in: nfd 54(2003) H.5, S.314 (W. Ratzek): "Um entscheidungsrelevante Daten aus der ständig wachsenden Flut von mehr oder weniger relevanten Dokumenten zu extrahieren, müssen Unternehmen, öffentliche Verwaltung oder Einrichtungen der Fachinformation effektive und effiziente Filtersysteme entwickeln, einsetzen und pflegen. Das vorliegende Lehrbuch von Holger Nohr bietet erstmalig eine grundlegende Einführung in das Thema "automatische Indexierung". Denn: "Wie man Information sammelt, verwaltet und verwendet, wird darüber entscheiden, ob man zu den Gewinnern oder Verlierern gehört" (Bill Gates), heißt es einleitend. Im ersten Kapitel "Einleitung" stehen die Grundlagen im Mittelpunkt. Die Zusammenhänge zwischen Dokumenten-Management-Systeme, Information Retrieval und Indexierung für Planungs-, Entscheidungs- oder Innovationsprozesse, sowohl in Profit- als auch Non-Profit-Organisationen werden beschrieben. Am Ende des einleitenden Kapitels geht Nohr auf die Diskussion um die intellektuelle und automatische Indexierung ein und leitet damit über zum zweiten Kapitel "automatisches Indexieren. Hier geht der Autor überblickartig unter anderem ein auf - Probleme der automatischen Sprachverarbeitung und Indexierung - verschiedene Verfahren der automatischen Indexierung z.B. einfache Stichwortextraktion / Volltextinvertierung, - statistische Verfahren, Pattern-Matching-Verfahren. Die "Verfahren der automatischen Indexierung" behandelt Nohr dann vertiefend und mit vielen Beispielen versehen im umfangreichsten dritten Kapitel. Das vierte Kapitel "Keyphrase Extraction" nimmt eine Passpartout-Status ein: "Eine Zwischenstufe auf dem Weg von der automatischen Indexierung hin zur automatischen Generierung textueller Zusammenfassungen (Automatic Text Summarization) stellen Ansätze dar, die Schlüsselphrasen aus Dokumenten extrahieren (Keyphrase Extraction). Die Grenzen zwischen den automatischen Verfahren der Indexierung und denen des Text Summarization sind fließend." (S. 91). Am Beispiel NCR"s Extractor/Copernic Summarizer beschreibt Nohr die Funktionsweise.
  12. Lück, W.; Rittberger, W.; Schwantner, M.: ¬Der Einsatz des Automatischen Indexierungs- und Retrievalsystems (AIR) im Fachinformationszentrum Karlsruhe (1994) 0.02
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  13. Yongcheng, W.; Xiaoming, G.; Lixia, W.: Automatic indexing on subject of Chinese text (1998) 0.02
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  14. Schneider, C.; Womser-Hacker, C.: Inhaltserschließungssysteme für Patenttexte : Test und Systemvergleich im Projekt PADOK (1986) 0.02
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  15. 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
  16. Jones, K.P.: Natural-language processing and automatic indexing : a reply (1990) 0.02
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    Footnote
    Erwiderung auf: Korycinski, C. u. A.F. Newell
  17. Lück, W.: Erfahrungen mit dem automatischen Indexierungssystem AIR/PHYS (1988) 0.01
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  18. Dresler, W.: Semi-automatische Indexierungssoftware : Möglichkeiten und Grenzen am Beispiel von g.a.d.t.1 (1998) 0.01
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  19. Fuhr, N.; Niewelt, B.: ¬Ein Retrievaltest mit automatisch indexierten Dokumenten (1984) 0.01
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    Date
    20.10.2000 12:22:23
  20. Hlava, M.M.K.: Automatic indexing : comparing rule-based and statistics-based indexing systems (2005) 0.01
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    Source
    Information outlook. 9(2005) no.8, S.22-23

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