Search (179 results, page 1 of 9)

  • × theme_ss:"Automatisches Indexieren"
  1. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.10
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
  2. Biebricher, N.; Fuhr, N.; Lustig, G.; Schwantner, M.; Knorz, G.: ¬The automatic indexing system AIR/PHYS : from research to application (1988) 0.07
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    Date
    16. 8.1998 12:51:22
    Footnote
    Wiederabgedruckt in: Readings in information retrieval. Ed.: K. Sparck Jones u. P. Willett. San Francisco: Morgan Kaufmann 1997. S.513-517.
    Source
    Proceedings of the 11th annual conference on research and development in information retrieval. Ed.: Y. Chiaramella
  3. Hodges, P.R.: Keyword in title indexes : effectiveness of retrieval in computer searches (1983) 0.06
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    Abstract
    A study was done to test the effectiveness of retrieval using title word searching. It was based on actual search profiles used in the Mechanized Information Center at Ohio State University, in order ro replicate as closely as possible actual searching conditions. Fewer than 50% of the relevant titles were retrieved by keywords in titles. The low rate of retrieval can be attributes to three sources: titles themselves, user and information specialist ignorance of the subject vocabulary in use, and to general language problems. Across fields it was found that the social sciences had the best retrieval rate, with science having the next best, and arts and humanities the lowest. Ways to enhance and supplement keyword in title searching on the computer and in printed indexes are discussed.
    Date
    14. 3.1996 13:22:21
  4. Bordoni, L.; Pazienza, M.T.: Documents automatic indexing in an environmental domain (1997) 0.05
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    Abstract
    Describes an application of Natural Language Processing (NLP) techniques, in HIRMA (Hypertextual Information Retrieval Managed by ARIOSTO), to the problem of document indexing by referring to a system which incorporates natural language processing techniques to determine the subject of the text of documents and to associate them with relevant semantic indexes. Describes briefly the overall system, details of its implementation on a corpus of scientific abstracts related to environmental topics and experimental evidence of the system's behaviour. Analyzes in detail an experiment designed to evaluate the system's retrieval ability in terms of recall and precision
    Source
    International forum on information and documentation. 22(1997) no.1, S.17-28
  5. Lepsky, K.; Vorhauer, J.: Lingo - ein open source System für die Automatische Indexierung deutschsprachiger Dokumente (2006) 0.05
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    Abstract
    Lingo ist ein frei verfügbares System (open source) zur automatischen Indexierung der deutschen Sprache. Bei der Entwicklung von lingo standen hohe Konfigurierbarkeit und Flexibilität des Systems für unterschiedliche Einsatzmöglichkeiten im Vordergrund. Der Beitrag zeigt den Nutzen einer linguistisch basierten automatischen Indexierung für das Information Retrieval auf. Die für eine Retrievalverbesserung zur Verfügung stehende linguistische Funktionalität von lingo wird vorgestellt und an Beispielen erläutert: Grundformerkennung, Kompositumerkennung bzw. Kompositumzerlegung, Wortrelationierung, lexikalische und algorithmische Mehrwortgruppenerkennung, OCR-Fehlerkorrektur. Der offene Systemaufbau von lingo wird beschrieben, mögliche Einsatzszenarien und Anwendungsgrenzen werden benannt.
    Date
    24. 3.2006 12:22:02
  6. Probst, M.; Mittelbach, J.: Maschinelle Indexierung in der Sacherschließung wissenschaftlicher Bibliotheken (2006) 0.05
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    Abstract
    Obwohl fast alle größeren Bibliotheken intellektuelle Sacherschließung betreiben, sind elektronische Kataloge für die zielgerichtete sachliche Suche nur eingeschränkt nutzbar. Durch maschinelle Indexierung können ohne nennenswerten personellen Mehraufwand ausreichend große Datenmengen für Informationsretrievalsysteme erzeugt und somit die Auffindbarkeit von Dokumenten erhöht werden. Geeignete Sprachanalysetechniken zur Indextermerzeugung sind bekannt und bieten im Gegensatz zur gebräuchlichen Freitextinvertierung entscheidende Vorteile beim Retrieval. Im Fokus steht die Betrachtung der Vor- und Nachteile der gängigen Indexierungssysteme MILOS und intelligentCAPTURE.
    Date
    22. 3.2008 12:35:19
  7. Renz, M.: Automatische Inhaltserschließung im Zeichen von Wissensmanagement (2001) 0.04
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    Abstract
    Methoden der automatischen Inhaltserschließung werden seit mehr als 30 Jahren entwickelt, ohne in luD-Kreisen auf merkliche Akzeptanz zu stoßen. Gegenwärtig führen jedoch die steigende Informationsflut und der Bedarf an effizienten Zugriffsverfahren im Informations- und Wissensmanagement in breiten Anwenderkreisen zu einem wachsenden Interesse an diesen Methoden, zu verstärkten Anstrengungen in Forschung und Entwicklung und zu neuen Produkten. In diesem Beitrag werden verschiedene Ansätze zu intelligentem und inhaltsbasiertem Retrieval und zur automatischen Inhaltserschließung diskutiert sowie kommerziell vertriebene Softwarewerkzeuge und Lösungen präsentiert. Abschließend wird festgestellt, dass in naher Zukunft mit einer zunehmenden Automatisierung von bestimmten Komponenten des Informations- und Wissensmanagements zu rechnen ist, indem Software-Werkzeuge zur automatischen Inhaltserschließung in den Workflow integriert werden
    Date
    22. 3.2001 13:14:48
  8. Plaunt, C.; Norgard, B.A.: ¬An association-based method for automatic indexing with a controlled vocabulary (1998) 0.03
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    Abstract
    In this article, we describe and test a two-stage algorithm based on a lexical collocation technique which maps from the lexical clues contained in a document representation into a controlled vocabulary list of subject headings. Using a collection of 4.626 INSPEC documents, we create a 'dictionary' of associations between the lexical items contained in the titles, authors, and abstracts, and controlled vocabulary subject headings assigned to those records by human indexers using a likelihood ratio statistic as the measure of association. In the deployment stage, we use the dictiony to predict which of the controlled vocabulary subject headings best describe new documents when they are presented to the system. Our evaluation of this algorithm, in which we compare the automatically assigned subject headings to the subject headings assigned to the test documents by human catalogers, shows that we can obtain results comparable to, and consistent with, human cataloging. In effect we have cast this as a classic partial match information retrieval problem. We consider the problem to be one of 'retrieving' (or assigning) the most probably 'relevant' (or correct) controlled vocabulary subject headings to a document based on the clues contained in that document
    Date
    11. 9.2000 19:53:22
  9. Milstead, J.L.: Thesauri in a full-text world (1998) 0.03
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    Date
    22. 9.1997 19:16:05
    Theme
    Verbale Doksprachen im Online-Retrieval
  10. Jardine, N.; Rijsbergen, C.J. van: ¬The use of hierarchic clustering in information retrieval (1971) 0.03
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    Source
    Information storage and retrieval. 7(1971), S.217-240
  11. Sparck Jones, K.; Jackson, D.M.: ¬The use of automatically obtained keyword classification for information retrieval (1970) 0.03
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    Source
    Information storage and retrieval. 5(1970), S.175-201
  12. Kantor, P.B.; Voorhees, E.: Information retrieval with scanned texts (2000) 0.03
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    Source
    Information retrieval. 2(2000), S.165-176
  13. Salton, G.: Another look at automatic text-retrieval systems (1986) 0.03
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    Footnote
    Bezugnahme auf: Blair, D.C.: An evaluation of retrieval effectiveness for a full-text document-retrieval system. Comm. ACM 28(1985) S.280-299. - Vgl. auch: Blair, D.C.: Full text retrieval ... Int. Class. 13(1986) S.18-23; Blair, D.C., M.E. Maron: full-text information retrieval ... Inf. Proc. Man. 26(1990) S.437-447.
  14. RIAO 91 : Computer aided information retrieval. Conference, Barcelona, 2.-4.5.1991 (1991) 0.03
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  15. Sparck Jones, K.: Automatic keyword classification for information retrieval (1971) 0.03
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  16. Fuhr, N.; Niewelt, B.: ¬Ein Retrievaltest mit automatisch indexierten Dokumenten (1984) 0.02
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    Date
    20.10.2000 12:22:23
  17. 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
  18. 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.
  19. 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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    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
  20. Salton, G.; McGill, M. J.: Information Retrieval: Grundlegendes für Informationswissenschaftler (1987) 0.02
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    Content
    Enthält die Kapitel: Information Retrieval: eine Einführung; Invertierte Dateisysteme; Textanalyse und automatisches Indexieren; Die experimentellen Retrievalsysteme SMART und SIRE; Die Bewertung von Retrievalsystemen; Fortgeschrittene Retrievaltechniken; Verarbeitung natürlicher Sprache; Informationstechnologie: Hardware und Software; Datenbankmanagementsysteme; Zukünftige Entwicklungen im Information Retrieval

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