Search (309 results, page 2 of 16)

  • × theme_ss:"Automatisches Indexieren"
  1. Groß, T.; Faden, M.: Automatische Indexierung elektronischer Dokumente an der Deutschen Zentralbibliothek für Wirtschaftswissenschaften : Bericht über die Jahrestagung der Internationalen Buchwissenschaftlichen Gesellschaft (2010) 0.01
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    Abstract
    Die zunehmende Verfügbarmachung digitaler Informationen in den letzten Jahren sowie die Aussicht auf ein weiteres Ansteigen der sogenannten Datenflut kumulieren in einem grundlegenden, sich weiter verstärkenden Informationsstrukturierungsproblem. Die stetige Zunahme von digitalen Informationsressourcen im World Wide Web sichert zwar jederzeit und ortsungebunden den Zugriff auf verschiedene Informationen; offen bleibt der strukturierte Zugang, insbesondere zu wissenschaftlichen Ressourcen. Angesichts der steigenden Anzahl elektronischer Inhalte und vor dem Hintergrund stagnierender bzw. knapper werdender personeller Ressourcen in der Sacherschließun schafft keine Bibliothek bzw. kein Bibliotheksverbund es mehr, weder aktuell noch zukünftig, alle digitalen Daten zu erfassen, zu strukturieren und zueinander in Beziehung zu setzen. In der Informationsgesellschaft des 21. Jahrhunderts wird es aber zunehmend wichtiger, die in der Flut verschwundenen wissenschaftlichen Informationen zeitnah, angemessen und vollständig zu strukturieren und somit als Basis für eine Wissensgenerierung wieder nutzbar zu machen. Eine normierte Inhaltserschließung digitaler Informationsressourcen ist deshalb für die Deutsche Zentralbibliothek für Wirtschaftswissenschaften (ZBW) als wichtige Informationsinfrastruktureinrichtung in diesem Bereich ein entscheidender und auch erfolgskritischer Aspekt im Wettbewerb mit anderen Informationsdienstleistern. Weil die traditionelle intellektuelle Sacherschließung aber nicht beliebig skalierbar ist - mit dem Anstieg der Zahl an Online-Dokumenten steigt proportional auch der personelle Ressourcenbedarf an Fachreferenten, wenn ein gewisser Qualitätsstandard gehalten werden soll - bedarf es zukünftig anderer Sacherschließungsverfahren. Automatisierte Verschlagwortungsmethoden werden dabei als einzige Möglichkeit angesehen, die bibliothekarische Sacherschließung auch im digitalen Zeitalter zukunftsfest auszugestalten. Zudem können maschinelle Ansätze dazu beitragen, die Heterogenitäten (Indexierungsinkonsistenzen) zwischen den einzelnen Sacherschließer zu nivellieren, und somit zu einer homogeneren Erschließung des Bibliotheksbestandes beitragen.
  2. Hodges, P.R.: Keyword in title indexes : effectiveness of retrieval in computer searches (1983) 0.01
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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
  3. Jardine, N.; Rijsbergen, C.J. van: ¬The use of hierarchic clustering in information retrieval (1971) 0.01
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    Source
    Information storage and retrieval. 7(1971), S.217-240
  4. Sparck Jones, K.; Jackson, D.M.: ¬The use of automatically obtained keyword classification for information retrieval (1970) 0.01
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    Source
    Information storage and retrieval. 5(1970), S.175-201
  5. Kantor, P.B.; Voorhees, E.: Information retrieval with scanned texts (2000) 0.01
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    Source
    Information retrieval. 2(2000), S.165-176
  6. RIAO 91 : Computer aided information retrieval. Conference, Barcelona, 2.-4.5.1991 (1991) 0.01
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  7. Sparck Jones, K.: Automatic keyword classification for information retrieval (1971) 0.01
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  8. Salton, G.: Another look at automatic text-retrieval systems (1986) 0.01
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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.
  9. Alexander, M.: Retrieving digital data with fuzzy matching (1996) 0.01
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    Abstract
    Briefly describes the Excalibur EFS system which makes use of adaptive pattern recognition technology as an aid to automatic indexing and how it is being tested at the British Library for the indexing and retrieval of scanned images from the library's holdings. Notes how Excalibur EFS can support a wide degree of fuzzy searching, compensate for the errors produced by OCR conversion of scanned images, reduce the costs of indexing, and require far less storage space than more traditional indexes
  10. Bordoni, L.; Pazienza, M.T.: Documents automatic indexing in an environmental domain (1997) 0.01
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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
  11. Dattola, R.T.: FIRST: Flexible information retrieval system for text (1979) 0.01
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    Source
    Journal of the American Society for Information Science. 30(1979), S.9-14
  12. Garfield, E.; Sager, N.: Mechanical indexing, structural linguistics and information retrieval (1993) 0.01
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    Source
    Journal of information science. 19(1993) no.2, S.164-165
  13. Daudaravicius, V.: ¬A framework for keyphrase extraction from scientific journals (2016) 0.01
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    Content
    Vortrag, "Semantics, Analytics, Visualisation: Enhancing Scholarly Data Workshop co-located with the 25th International World Wide Web Conference April 11, 2016 - Montreal, Canada", Montreal 2016.
  14. Salton, G.; McGill, M. J.: Information Retrieval: Grundlegendes für Informationswissenschaftler (1987) 0.01
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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
  15. Salton, G.: Automatic text processing : the transformation, analysis, and retrieval of information by computer (1989) 0.01
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    COMPASS
    Information retrieval / Use of / On-line computers
    Subject
    Information retrieval / Use of / On-line computers
  16. Lepsky, K.; Vorhauer, J.: Lingo - ein open source System für die Automatische Indexierung deutschsprachiger Dokumente (2006) 0.01
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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
  17. Salton, G.; McGill, M. J.: Introduction to modern information retrieval (1983) 0.01
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  18. Research and development in information retrieval : Proc., Berlin, 18.-20.5.1982 (1983) 0.01
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  19. Gray, W.A.; Harley, A.J.: Computer assisted indexing (1971) 0.01
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    Source
    Information storage and retrieval. 7(1971), S.167-174
  20. Stiles, H.E.: ¬The association factor in information retrieval (1961) 0.01
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Languages

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  • el 16
  • m 15
  • s 9
  • d 2
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