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  • × year_i:[2000 TO 2010}
  • × theme_ss:"Retrievalstudien"
  1. Buckley, C.; Voorhees, E.M.: Retrieval system evaluation (2005) 0.03
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    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  2. Buckley, C.: ¬The SMART Project at TREC (2005) 0.02
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    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  3. ¬The Eleventh Text Retrieval Conference, TREC 2002 (2003) 0.02
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    Abstract
    Proceedings of the llth TREC-conference held in Gaithersburg, Maryland (USA), November 19-22, 2002. Aim of the conference was discussion an retrieval and related information-seeking tasks for large test collection. 93 research groups used different techniques, for information retrieval from the same large database. This procedure makes it possible to compare the results. The tasks are: Cross-language searching, filtering, interactive searching, searching for novelty, question answering, searching for video shots, and Web searching.
    Editor
    Voorhees, E.M. u. D.K. Harman
  4. Kluck, M.; Winter, M.: Topic-Entwicklung und Relevanzbewertung bei GIRT : ein Werkstattbericht (2006) 0.02
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    Source
    Effektive Information Retrieval Verfahren in Theorie und Praxis: ausgewählte und erweiterte Beiträge des Vierten Hildesheimer Evaluierungs- und Retrievalworkshop (HIER 2005), Hildesheim, 20.7.2005. Hrsg.: T. Mandl u. C. Womser-Hacker
  5. Mandl, T.: Neue Entwicklungen bei den Evaluierungsinitiativen im Information Retrieval (2006) 0.02
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    Source
    Effektive Information Retrieval Verfahren in Theorie und Praxis: ausgewählte und erweiterte Beiträge des Vierten Hildesheimer Evaluierungs- und Retrievalworkshop (HIER 2005), Hildesheim, 20.7.2005. Hrsg.: T. Mandl u. C. Womser-Hacker
  6. Ferret, O.; Grau, B.; Hurault-Plantet, M.; Illouz, G.; Jacquemin, C.; Monceaux, L.; Robba, I.; Vilnat, A.: How NLP can improve question answering (2002) 0.01
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  7. Blandford, A.; Adams, A.; Attfield, S.; Buchanan, G.; Gow, J.; Makri, S.; Rimmer, J.; Warwick, C.: ¬The PRET A Rapporter framework : evaluating digital libraries from the perspective of information work (2008) 0.01
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  8. Lioma, C.; Ounis, I.: ¬A syntactically-based query reformulation technique for information retrieval (2008) 0.01
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    Abstract
    Whereas in language words of high frequency are generally associated with low content [Bookstein, A., & Swanson, D. (1974). Probabilistic models for automatic indexing. Journal of the American Society of Information Science, 25(5), 312-318; Damerau, F. J. (1965). An experiment in automatic indexing. American Documentation, 16, 283-289; Harter, S. P. (1974). A probabilistic approach to automatic keyword indexing. PhD thesis, University of Chicago; Sparck-Jones, K. (1972). A statistical interpretation of term specificity and its application in retrieval. Journal of Documentation, 28, 11-21; Yu, C., & Salton, G. (1976). Precision weighting - an effective automatic indexing method. Journal of the Association for Computer Machinery (ACM), 23(1), 76-88], shallow syntactic fragments of high frequency generally correspond to lexical fragments of high content [Lioma, C., & Ounis, I. (2006). Examining the content load of part of speech blocks for information retrieval. In Proceedings of the international committee on computational linguistics and the association for computational linguistics (COLING/ACL 2006), Sydney, Australia]. We implement this finding to Information Retrieval, as follows. We present a novel automatic query reformulation technique, which is based on shallow syntactic evidence induced from various language samples, and used to enhance the performance of an Information Retrieval system. Firstly, we draw shallow syntactic evidence from language samples of varying size, and compare the effect of language sample size upon retrieval performance, when using our syntactically-based query reformulation (SQR) technique. Secondly, we compare SQR to a state-of-the-art probabilistic pseudo-relevance feedback technique. Additionally, we combine both techniques and evaluate their compatibility. We evaluate our proposed technique across two standard Text REtrieval Conference (TREC) English test collections, and three statistically different weighting models. Experimental results suggest that SQR markedly enhances retrieval performance, and is at least comparable to pseudo-relevance feedback. Notably, the combination of SQR and pseudo-relevance feedback further enhances retrieval performance considerably. These collective experimental results confirm the tenet that high frequency shallow syntactic fragments correspond to content-bearing lexical fragments.
  9. 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
  10. Harman, D.K.: ¬The TREC test collections (2005) 0.01
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    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  11. Harman, D.K.: ¬The TREC ad hoc experiments (2005) 0.01
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    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  12. Robertson, S.; Callan, J.: Routing and filtering (2005) 0.01
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    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  13. Harman, D.K.: Beyond English (2005) 0.01
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    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  14. Voorhees, E.M.; Garofolo, J.S.: Retrieving noisy text (2005) 0.01
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    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
  15. Rapke, K.: Automatische Indexierung von Volltexten für die Gruner+Jahr Pressedatenbank (2001) 0.01
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    Abstract
    Retrievaltests 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 aufgrund 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
  16. Kazai, G.; Lalmas, M.: ¬The overlap problem in content-oriented XML retrieval evaluation (2004) 0.01
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  17. Womser-Hacker, C.: Theorie des Information Retrieval III : Evaluierung (2004) 0.01
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    Grundlagen der praktischen Information und Dokumentation. 5., völlig neu gefaßte Ausgabe. 2 Bde. Hrsg. von R. Kuhlen, Th. Seeger u. D. Strauch. Begründet von Klaus Laisiepen, Ernst Lutterbeck, Karl-Heinrich Meyer-Uhlenried. Bd.1: Handbuch zur Einführung in die Informationswissenschaft und -praxis
  18. 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
  19. 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
  20. Dumais, S.T.; Belkin, N.J.: ¬The TREC interactive tracks : putting the user into search (2005) 0.01
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    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman

Languages

  • e 38
  • d 9
  • m 1
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Types

  • a 45
  • m 3
  • s 3
  • r 1
  • More… Less…