Search (52 results, page 1 of 3)

  • × theme_ss:"Retrievalstudien"
  • × type_ss:"a"
  • × year_i:[2000 TO 2010}
  1. Allan, J.; Croft, W.B.; Callan, J.: ¬The University of Massachusetts and a dozen TRECs (2005) 0.05 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  2. Robertson, S.; Callan, J.: Routing and filtering (2005) 0.05 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  3. Griesbaum, J.; Rittberger, M.; Bekavac, B.: Deutsche Suchmaschinen im Vergleich : AltaVista.de, Fireball.de, Google.de und Lycos.de (2002) 0.04 
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  4. Larsen, B.; Ingwersen, P.; Lund, B.: Data fusion according to the principle of polyrepresentation (2009) 0.02 
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    Date
    22. 3.2009 18:48:28
  5. Harman, D.K.: ¬The TREC test collections (2005) 0.01 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  6. Buckley, C.; Voorhees, E.M.: Retrieval system evaluation (2005) 0.01 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  7. Harman, D.K.: ¬The TREC ad hoc experiments (2005) 0.01 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  8. Harman, D.K.: Beyond English (2005) 0.01 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  9. Voorhees, E.M.; Garofolo, J.S.: Retrieving noisy text (2005) 0.01 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  10. Voorhees, E.M.: Question answering in TREC (2005) 0.01 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  11. Cormack, G.V.; Clarke, C.L.A.; Palmer, C.R.; Lynam, T.R.: MultiText experiments for TREC (2005) 0.01 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  12. Dumais, S.T.; Belkin, N.J.: ¬The TREC interactive tracks : putting the user into search (2005) 0.01 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  13. Hawking, D.; Craswell, N.: ¬The very large collection and Web tracks (2005) 0.01 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  14. Robertson, S.: How Okapi came to TREC (2005) 0.01 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  15. Buckley, C.: ¬The SMART Project at TREC (2005) 0.01 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  16. Kwok, K.-L.: Ten years of ad hoc retrieval at TREC using PIRCS (2005) 0.01 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  17. Hiemstra, D.; Kraaij, W.: ¬A language-modeling approach to TREC (2005) 0.01 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  18. Sparck Jones, K.: Metareflections on TREC (2005) 0.01 
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    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  19. Schoger, A.; Frommer, J.: Heterogen - was nun? : Evaluierung heterogener bibliographischer Metadaten (2000) 0.01 
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  20. Rapke, K.: Automatische Indexierung von Volltexten für die Gruner+Jahr Pressedatenbank (2001) 0.01 
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    Abstract
    Retrieval Tests sind die anerkannteste Methode, um neue Verfahren der Inhaltserschließung gegenüber traditionellen Verfahren zu rechtfertigen. Im Rahmen einer Diplomarbeit wurden zwei grundsätzlich unterschiedliche Systeme der automatischen inhaltlichen Erschließung anhand der Pressedatenbank des Verlagshauses Gruner + Jahr (G+J) getestet und evaluiert. Untersucht wurde dabei natürlichsprachliches Retrieval im Vergleich zu Booleschem Retrieval. Bei den beiden Systemen handelt es sich zum einen um Autonomy von Autonomy Inc. und DocCat, das von IBM an die Datenbankstruktur der G+J Pressedatenbank angepasst wurde. Ersteres ist ein auf natürlichsprachlichem Retrieval basierendes, probabilistisches System. DocCat demgegenüber basiert auf Booleschem Retrieval und ist ein lernendes System, das auf Grund einer intellektuell erstellten Trainingsvorlage indexiert. Methodisch geht die Evaluation vom realen Anwendungskontext der Textdokumentation von G+J aus. Die Tests werden sowohl unter statistischen wie auch qualitativen Gesichtspunkten bewertet. Ein Ergebnis der Tests ist, dass DocCat einige Mängel gegenüber der intellektuellen Inhaltserschließung aufweist, die noch behoben werden müssen, während das natürlichsprachliche Retrieval von Autonomy in diesem Rahmen und für die speziellen Anforderungen der G+J Textdokumentation so nicht einsetzbar ist

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  • d 10

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