Search (55 results, page 3 of 3)

  • × theme_ss:"Retrievalstudien"
  • × year_i:[1990 TO 2000}
  1. Beaulieu, M.; Robertson, S.; Rasmussen, E.: Evaluating interactive systems in TREC (1996) 0.01 
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  2. Iivonen, M.: Factors lowering the consistency in online searching (1995) 0.01 
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  3. Wan, T.-L.; Evens, M.; Wan, Y.-W.; Pao, Y.-Y.: Experiments with automatic indexing and a relational thesaurus in a Chinese information retrieval system (1997) 0.01 
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  4. Salampasis, M.; Tait, J.; Bloor, C.: Evaluation of information-seeking performance in hypermedia digital libraries (1998) 0.01 
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  5. Sachse, E.; Liebig, M.; Gödert, W.: Automatische Indexierung unter Einbeziehung semantischer Relationen : Ergebnisse des Retrievaltests zum MILOS II-Projekt (1998) 0.01 
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  6. Gödert, W.; Liebig, M.: Maschinelle Indexierung auf dem Prüfstand : Ergebnisse eines Retrievaltests zum MILOS II Projekt (1997) 0.01 
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  7. Gluck, M.: Understanding performance in information systems : blending relevance and competence (1995) 0.00 
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  8. Shafique, M.; Chaudhry, A.S.: Intelligent agent-based online information retrieval (1995) 0.00 
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  9. Shakir, H.S.; Nagao, M.: Context-sensitive processing of semantic queries in an image database system (1996) 0.00 
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  10. Drabenstott, K.M.; Vizine-Goetz, D.: Using subject headings for online retrieval : theory, practice and potential (1994) 0.00 
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  11. ¬The Second Text Retrieval Conference : TREC-2 (1995) 0.00 
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    Content
    Enthält die Beiträge: HARMAN, D.: Overview of the Second Text Retrieval Conference (TREC-2); SPRACK JONES, K.: Reflections on TREC; BUCKLEY, C., J. ALLAN u. G. SALTON: Automatic routing and retrieval using SMART: TREC-2; CALLAN, J.P., W.B. CROFT u. J. BROGLIO: TREC and TIPSTER experiments with INQUERY; ROBERTSON, S.R., S. WALKER u. M.M. HANCOCK-BEAULIEU: Large test collection experiments on an operational, interactive system: OKAPI at TREC; ZOBEL, J., A. MOFFAT, R. WILKINSON u. R. SACKS-DAVIS: Efficient retrieval of partial documents; METTLER, M. u. F. NORDBY: TREC routing experiments with the TRW/Paracel Fast Data Finder; EVANS, D.A. u. R.G. LEFFERTS: CLARIT-TREC experiments; STRZALKOWSKI, T.: Natural language information retrieval; CAID, W.R., S.T. DUMAIS u. S.I. GALLANT: Learned vector-space models for document retrieval; BELKIN, N.J. P. KANTOR, E.A. FOX u. J.A. SHAW: Combining the evidence of multiple query representations for information retrieval
  12. Gluck, M.: Exploring the relationship between user satisfaction and relevance in information systems (1996) 0.00 
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  13. Wildemuth, B.M.; Jacob, E.K.; Fullington, A.;; Bliek, R. de; Friedman, C.P.: ¬A detailed analysis of end-user search behaviours (1991) 0.00 
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    Source
    ASIS'91: systems understanding people. Proc. of the 54th Annual Meeting of the ASIS, vol.28, Washington, DC, 27.-31.10.1991. Ed.: J.-M. Griffiths
  14. Robertson, S.E.; Sparck Jones, K.: Simple, proven approaches to text retrieval (1997) 0.00 
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    Abstract
    This technical note describes straightforward techniques for document indexing and retrieval that have been solidly established through extensive testing and are easy to apply. They are useful for many different types of text material, are viable for very large files, and have the advantage that they do not require special skills or training for searching, but are easy for end users. The document and text retrieval methods described here have a sound theoretical basis, are well established by extensive testing, and the ideas involved are now implemented in some commercial retrieval systems. Testing in the last few years has, in particular, shown that the methods presented here work very well with full texts, not only title and abstracts, and with large files of texts containing three quarters of a million documents. These tests, the TREC Tests (see Harman 1993 - 1997; IP&M 1995), have been rigorous comparative evaluations involving many different approaches to information retrieval. These techniques depend an the use of simple terms for indexing both request and document texts; an term weighting exploiting statistical information about term occurrences; an scoring for request-document matching, using these weights, to obtain a ranked search output; and an relevance feedback to modify request weights or term sets in iterative searching. The normal implementation is via an inverted file organisation using a term list with linked document identifiers, plus counting data, and pointers to the actual texts. The user's request can be a word list, phrases, sentences or extended text.
  15. Cross-language information retrieval (1998) 0.00 
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    Type
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