Search (92 results, page 5 of 5)

  • × theme_ss:"Retrievalstudien"
  1. Munkelt, J.; Schaer, P.; Lepsky, K.: Towards an IR test collection for the German National Library (2018) 0.01 
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    Date
    21. 6.2018 15:58:28
  2. Meyer, O.C.: Retrievalexperimente mit bibliothekarischen Daten : Historischer Überblick und aktueller Forschungsstand (2022) 0.01 
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    Date
    17. 8.2022 13:21:30
  3. Larsen, B.; Ingwersen, P.; Lund, B.: Data fusion according to the principle of polyrepresentation (2009) 0.01 
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    Date
    22. 3.2009 18:48:28
  4. Greisdorf, H.; O'Connor, B.: Nodes of topicality modeling user notions of on topic documents (2003) 0.01 
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    Abstract
    Griesdorf and O'Connor attempt to determine the aspects of a retrieved item that provide a questioner with evidence that the item is in fact on the topic searched independent of its relevance. To this end they collect data from 32 participants, 11 from the business community as well as 21 doctoral students at the University of North Texas each of whom were asked to state if they considered material that approaches a topic in each of 14 specific manners as " on topic" or "off topic." Chi-square indicates that the observed values are significantly different from expected values and the chi-square residuals for on topic judgements exceed plus or minus two in eight cases and plus two in five cases. The positive values which indicate a percentage of response greater than that from chance suggest that documents considered topical are only related to the problem at hand, contain terms that were in the query, and describe, explain or expand the topic of the query. The chi-square residuals for off topic judgements exceed plus or minus two in ten cases and plus two in four cases. The positive values suggest that documents considered not topical exhibit a contrasting, contrary, or confounding point of view, or merely spark curiosity. Such material might well be relevant, but is not judged topical. This suggests that topical appropriateness may best be achieved using the Bruza, et alia, left compositional monotonicity approach.
  5. Eastman, C.M.: 30,000 hits may be better than 300 : precision anomalies in Internet searches (2002) 0.01 
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    Date
    21. 7.2006 13:54:10
  6. Scherer, B.: Automatische Indexierung und ihre Anwendung im DFG-Projekt "Gemeinsames Portal für Bibliotheken, Archive und Museen (BAM)" (2003) 0.01 
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    Date
    14. 3.2003 21:11:31
  7. Schaer, P.; Mayr, P.; Sünkler, S.; Lewandowski, D.: How relevant is the long tail? : a relevance assessment study on million short (2016) 0.01 
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    Date
    18.10.2016 12:59:21
  8. Behnert, C.; Lewandowski, D.: ¬A framework for designing retrieval effectiveness studies of library information systems using human relevance assessments (2017) 0.01 
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    Date
    26. 6.2017 13:21:04
  9. Toepfer, M.; Seifert, C.: Content-based quality estimation for automatic subject indexing of short texts under precision and recall constraints 0.01 
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    Date
    21. 6.2018 12:03:43
  10. Vegt, A. van der; Zuccon, G.; Koopman, B.: Do better search engines really equate to better clinical decisions? : If not, why not? (2021) 0.01 
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    Date
    21. 1.2021 11:06:16
  11. Lioma, C.; Ounis, I.: ¬A syntactically-based query reformulation technique for information retrieval (2008) 0.00 
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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.
  12. Cross-language information retrieval (1998) 0.00 
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    Date
    21. 6.2005 21:19:49

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