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  • × theme_ss:"Automatisches Indexieren"
  1. RIAO 91 : Computer aided information retrieval. Conference, Barcelona, 2.-4.5.1991 (1991) 0.05 
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  2. Silvester, J.P.: Computer supported indexing : a history and evaluation of NASA's MAI system (1998) 0.03 
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    Pages
    S.76-91
  3. 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.
  4. Clavel, G.; Walther, F.; Walther, J.: Indexation automatique de fonds bibliotheconomiques (1993) 0.02 
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    Abstract
    A discussion of developments to date in the field of computerized indexing, based on presentations given at a seminar held at the Institute of Policy Studies in Paris in Nov 91. The methods tested so far, based on a linguistic approach, whether using natural language or special thesauri, encounter the same central problem - they are only successful when applied to collections of similar types of documents covering very specific subject areas. Despite this, the search for some sort of universal indexing metalanguage continues. In the end, computerized indexing works best when used in conjunction with manual indexing - ideally in the hands of a trained library science professional, who can extract the maximum value from a collection of documents for a particular user population
  5. Schneider, C.; Womser-Hacker, C.: Inhaltserschließungssysteme für Patenttexte : Test und Systemvergleich im Projekt PADOK (1986) 0.02 
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  6. Jones, K.P.: Natural-language processing and automatic indexing : a reply (1990) 0.01 
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    Footnote
    Erwiderung auf: Korycinski, C. u. A.F. Newell
  7. Gibb, F.; Smart, G.: Knowledge-based indexing : the view from SIMPR (1991) 0.01 
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    Source
    Libraries and expert systems. Ed. C. MacDonald et al
  8. Schwarz, C.: Komplexe Nominalgruppen als Indexierungseinheiten am Beispiel des Projekte CONDOR (1982) 0.01 
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  9. Salton, G.; Allen, J.; Buckley, C.; Singhal, A.: Automatic analysis, theme generation, and summarization of machine-readable data (1994) 0.01 
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  10. Schröther, C.: Automatische Indexierung, Kategorisierung und inhaltliche Erschließung von Textnachrichten (2003) 0.01 
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  11. 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) 0.01 
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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
  12. 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
  13. Salton, G.; Allan, J.; Buckley, C.; Singhal, A.: Automatic analysis, theme generation, and summarization of machine readable texts (1994) 0.01 
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  14. 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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    Source
    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
  15. Rasmussen, E.M.: Indexing and retrieval for the Web (2002) 0.01 
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    Source
    Annual review of information science and technology. 37(2003), S.91-126
  16. Koryconski, C.; Newell, A.F.: Natural-language processing and automatic indexing (1990) 0.01 
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  17. Salton, G.; Buckley, C.; Allan, J.: Automatic structuring of text files (1992) 0.01 
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  18. Abdul, H.; Khoo, C.: Automatic indexing of medical literature using phrase matching : an exploratory study 0.01 
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  19. Krause, J.; Womser-Hacker, C.: PADOK-II : Retrievaltests zur Bewertung von Volltextindexierungsvarianten für das deutsche Patentinformationssystem (1990) 0.01 
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  20. Fox, C.: Lexical analysis and stoplists (1992) 0.01 
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