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  1. Rajagopal, P.; Ravana, S.D.; Koh, Y.S.; Balakrishnan, V.: Evaluating the effectiveness of information retrieval systems using effort-based relevance judgment (2019) 0.00
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    Date
    20. 1.2015 18:30:22
    Source
    Aslib journal of information management. 71(2019) no.1, S.2-17
  2. Hancock-Beaulieu, M.; McKenzie, L.; Irving, A.: Evaluative protocols for searching behaviour in online library catalogues (1991) 0.00
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    Date
    23. 1.1999 19:52:29
  3. Harman, D.K.: ¬The TREC test collections (2005) 0.00
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    Date
    29. 3.1996 18:16:49
  4. Buckley, C.; Voorhees, E.M.: Retrieval system evaluation (2005) 0.00
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    Date
    29. 3.1996 18:16:49
  5. Voiskunskii, V.G.: Evaluation of search results (2000) 0.00
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    Source
    Encyclopedia of library and information science. Vol.66, [=Suppl.29]
  6. Harman, D.K.: ¬The TREC ad hoc experiments (2005) 0.00
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    Date
    29. 3.1996 18:16:49
  7. Robertson, S.; Callan, J.: Routing and filtering (2005) 0.00
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    Date
    29. 3.1996 18:16:49
  8. Beaulieu, M.: Approaches to user-based studies in information seeking and retrieval : a Sheffield perspective (2003) 0.00
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    Source
    Journal of information science. 29(2003) no.4, S.239-248
  9. Harman, D.K.: Beyond English (2005) 0.00
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    Date
    29. 3.1996 18:16:49
  10. Voorhees, E.M.; Garofolo, J.S.: Retrieving noisy text (2005) 0.00
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    Date
    29. 3.1996 18:16:49
  11. Tomaiuolo, N.G.; Parker, J.: Maximizing relevant retrieval : keyword and natural language searching (1998) 0.00
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    Source
    Online. 22(1998) no.6, S.57-58
  12. Dalrymple, P.W.: Retrieval by reformulation in two library catalogs : toward a cognitive model of searching behavior (1990) 0.00
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    Date
    22. 7.2006 18:43:54
  13. 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.
    Source
    Information processing and management. 44(2008) no.1, S.143-162
  14. Croft, W.B.; Thompson, R.H.: Support for browsing in an intelligent text retrieval system (1989) 0.00
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    Source
    International journal of man-machine studies. 30(1989), S.639-668
  15. Cleverdon, C.W.; Mills, J.: ¬The testing of index language devices (1997) 0.00
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    Imprint
    The Hague : International Federation for Information and Documentation (FID)
    Source
    From classification to 'knowledge organization': Dorking revisited or 'past is prelude'. A collection of reprints to commemorate the firty year span between the Dorking Conference (First International Study Conference on Classification Research 1957) and the Sixth International Study Conference on Classification Research (London 1997). Ed.: A. Gilchrist
  16. Voorhees, E.M.: Question answering in TREC (2005) 0.00
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    Date
    29. 3.1996 18:16:49
  17. Cormack, G.V.; Clarke, C.L.A.; Palmer, C.R.; Lynam, T.R.: MultiText experiments for TREC (2005) 0.00
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    Date
    29. 3.1996 18:16:49
  18. Dumais, S.T.; Belkin, N.J.: ¬The TREC interactive tracks : putting the user into search (2005) 0.00
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    Date
    29. 3.1996 18:16:49
  19. Hawking, D.; Craswell, N.: ¬The very large collection and Web tracks (2005) 0.00
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    Date
    29. 3.1996 18:16:49
  20. Allan, J.; Croft, W.B.; Callan, J.: ¬The University of Massachusetts and a dozen TRECs (2005) 0.00
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    Date
    29. 3.1996 18:16:49

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