Search (54 results, page 1 of 3)

  • × year_i:[1990 TO 2000}
  • × theme_ss:"Retrievalstudien"
  1. Tomaiuolo, N.G.; Parker, J.: Maximizing relevant retrieval : keyword and natural language searching (1998) 0.05 
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    Source
    Online. 22(1998) no.6, S.57-58
  2. Allan, J.; Callan, J.P.; Croft, W.B.; Ballesteros, L.; Broglio, J.; Xu, J.; Shu, H.: INQUERY at TREC-5 (1997) 0.05 
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    Date
    27. 2.1999 20:55:22
  3. Pemberton, J.K.; Ojala, M.; Garman, N.: Head to head : searching the Web versus traditional services (1998) 0.04 
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    Source
    Online. 22(1998) no.3, S.24-26,28
  4. Wood, F.; Ford, N.; Miller, D.; Sobczyk, G.; Duffin, R.: Information skills, searching behaviour and cognitive styles for student-centred learning : a computer-assisted learning approach (1996) 0.03 
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    Source
    Journal of information science. 22(1996) no.2, S.79-92
  5. Evans, J.E.: Some external and internal factors affecting users of interactive information systems (1996) 0.03 
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    Abstract
    This contribution reports the results of continuing research in human-information system interactions. Following training and experience with an electronic information retrieval system novice and experienced subject groups responded to questions ranking their value assessments of 7 attributes of information sources in relation to 15 factors describing the search process. In general, novice users were more heavily influenced by the process factors (negative influences) than by the positive attributes of information qualities. Experienced users, while still concerned with process factors, were more strongly influenced by the qualitative information attributes. The specific advantages and contributions of this research are several: higher dimensionality of measured factors and attributes (15 x 7); higher granularity of analysis using a 7 value metric in a closed-end Likert scale; development of bi-directional, firced-choice influence vectors; and a larger sample size (N=186) than previously reported in the literature
    Source
    Herausforderungen an die Informationswirtschaft: Informationsverdichtung, Informationsbewertung und Datenvisualisierung. Proceedings des 5. Internationalen Symposiums für Informationswissenschaft (ISI'96), Humboldt-Universität zu Berlin, 17.-19. Oktober 1996. Hrsg.: J. Krause u.a
  6. Strzalkowski, T.; Guthrie, L.; Karlgren, J.; Leistensnider, J.; Lin, F.; Perez-Carballo, J.; Straszheim, T.; Wang, J.; Wilding, J.: Natural language information retrieval : TREC-5 report (1997) 0.02 
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  7. Dalrymple, P.W.: Retrieval by reformulation in two library catalogs : toward a cognitive model of searching behavior (1990) 0.01 
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    Date
    22. 7.2006 18:43:54
  8. Pfeifer, U.; Poersch, T.; Fuhr, N.: Retrieval effectiveness of proper name search methods (1996) 0.01 
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  9. Frei, H.P.; Meienberg, S.; Schäuble, P.: ¬The perils of interpreting recall and precision values (1991) 0.01 
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    Source
    Information retrieval: GI/GMD-Workshop, Darmstadt, 23.-24.6.1991: Proceedings. Ed.: N. Fuhr
  10. Callan, J.; Croft, W.B.; Broglio, J.: TREC and TIPSTER experiments with INQUERY (1995) 0.01 
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  11. Krause, J.; Mutschke, P.: Indexierung und Fulcrum-Evaluierung (1999) 0.01 
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  12. Tseng, Y.-H.: Solving vocabulary problems with interactive query expansion (1998) 0.01 
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    Abstract
    One of the major causes of search failures in information retrieval systems is vocabulary mismatch. Presents a solution to the vocabulary problem through 2 strategies known as term suggestion (TS) and term relevance feedback (TRF). In TS, collection specific terms are extracted from the text collection. These terms and their frequencies constitute the keyword database for suggesting terms in response to users' queries. One effect of this term suggestion is that it functions as a dynamic directory if the query is a general term that contains broad meaning. In term relevance feedback, terms extracted from the top ranked documents retrieved from the previous query are shown to users for relevance feedback. In the experiment, interactive TS provides very high precision rates while achieving similar recall rates as n-gram matching. Local TRF achieves improvement in both precision and recall rate in a full text news database and degrades slightly in recall rate in bibliographic databases due to the very limited source of information for feedback. In terms of Rijsbergen's combined measure of recall and precision, both TS and TRF achieve better performance than n-gram matching, which implies that the greater improvement in precision rate compensates the slight degradation in recall rate for TS and TRF
  13. Lancaster, F.W.; Connell, T.H.; Bishop, N.; McCowan, S.: Identifying barriers to effective subject access in library catalogs (1991) 0.01 
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  14. Ng, K.B.; Loewenstern, D.; Basu, C.; Hirsh, H.; Kantor, P.B.: Data fusion of machine-learning methods for the TREC5 routing tak (and other work) (1997) 0.01 
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    Date
    27. 2.1999 20:59:22
  15. Strzalkowski, T.; Perez-Carballo, J.: Natural language information retrieval : TREC-4 report (1996) 0.01 
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  16. Gauch, S.; Wang, J.: Corpus analysis for TREC 5 query expansion (1997) 0.01 
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  17. Cowie, J.; Guan, Z.: CRL English routing system for TREC-5 (1997) 0.01 
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  18. Savoy, J.; Calvé, A. le; Vrajitoru, D.: Report on the TREC5 experiment : data fusion and collection fusion (1997) 0.01 
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  19. Chevallet, J.-P.; Bruandet, M.F.: Impact de l'utilisation de multi terms sur la qualité des résponses dùn système de recherche d'information a indexation automatique (1999) 0.01 
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    Source
    Organisation des connaissances en vue de leur intégration dans les systèmes de représentation et de recherche d'information. Ed.: J. Maniez, et al
  20. Wood, F.; Ford, N.; Walsh, C.: ¬The effect of postings information on search behaviour (1994) 0.01 
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Authors

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