Search (135 results, page 2 of 7)

  • × theme_ss:"Retrievalstudien"
  • × year_i:[2000 TO 2010}
  1. Hiemstra, D.; Kraaij, W.: ¬A language-modeling approach to TREC (2005) 0.01
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    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
    Type
    a
  2. Wilbur, W.J.: Global term weights for document retrieval learned from TREC data (2001) 0.01
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    Source
    Journal of information science. 27(2001) no.5, S.303-310
    Type
    a
  3. Hersh, W.R.; Over, P.: Interactivity at the Text Retrieval Conference (TREC) (2001) 0.01
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    Source
    Information processing and management. 37(2001) no.3, S.365-367
    Type
    a
  4. Over, P.: ¬The TREC interactive track : an annotated bibliography (2001) 0.01
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    Source
    Information processing and management. 37(2001) no.3, S.369-381
    Type
    a
  5. Voorhees, E.M.: Variations in relevance judgements and the measurement of retrieval effectiveness (2000) 0.01
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    Source
    Information processing and management. 36(2000) no.5, S.697-716
    Type
    a
  6. 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
    Type
    a
  7. Buckley, C.; Voorhees, E.M.: Retrieval system evaluation (2005) 0.01
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    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
    Type
    a
  8. Voiskunskii, V.G.: Evaluation of search results (2000) 0.01
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    Source
    Encyclopedia of library and information science. Vol.66, [=Suppl.29]
    Type
    a
  9. 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
    Type
    a
  10. Smeaton, A.F.: TREC-6: personal highlights (2000) 0.01
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    Source
    Information processing and management. 36(2000) no.1, S.87-94
    Type
    a
  11. 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
    Type
    a
  12. 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
    Type
    a
  13. 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
    Type
    a
  14. Tague-Sutcliffe, J.: Information retrieval experimentation (2009) 0.01
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    Abstract
    Jean Tague-Sutcliffe was an important figure in information retrieval experimentation. Here, she reviews the history of IR research, and provides a description of the fundamental paradigm of information retrieval experimentation that continues to dominate the field.
    Source
    Encyclopedia of library and information sciences. 3rd ed. Ed.: M.J. Bates
    Type
    a
  15. Rokaya, M.; Atlam, E.; Fuketa, M.; Dorji, T.C.; Aoe, J.-i.: Ranking of field association terms using Co-word analysis (2008) 0.01
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    Abstract
    Information retrieval involves finding some desired information in a store of information or a database. In this paper, Co-word analysis will be used to achieve a ranking of a selected sample of FA terms. Based on this ranking a better arranging of search results can be achieved. Experimental results achieved using 41 MB of data (7660 documents) in the field of sports. The corpus was collected from CNN newspaper, sports field. This corpus was chosen to be distributed over 11 sub-fields of the field sports from the experimental results, the average precision increased by 18.3% after applying the proposed arranging scheme depending on the absolute frequency to count the terms weights, and the average precision increased by 17.2% after applying the proposed arranging scheme depending on a formula based on "TF*IDF" to count the terms weights.
    Source
    Information processing and management. 44(2008) no.2, S.738-755
    Type
    a
  16. Morse, E.; Lewis, M.; Olsen, K.A.: Testing visual information retrieval methodologies case study : comparative analysis of textual, icon, graphical, and "spring" displays (2002) 0.01
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    Abstract
    Although many different visual information retrieval systems have been proposed, few have been tested, and where testing has been performed, results were often inconclusive. Further, there is very little evidence of benchmarking systems against a common standard. An approach for testing novel interfaces is proposed that uses bottom-up, stepwise testing to allow evaluation of a visualization, itself, rather than restricting evaluation to the system instantiating it. This approach not only makes it easier to control variables, but the tests are also easier to perform. The methodology will be presented through a case study, where a new visualization technique is compared to more traditional ways of presenting data
    Source
    Journal of the American Society for Information Science and technology. 53(2002) no.1, S.28-40
    Type
    a
  17. Serrano Cobos, J.; Quintero Orta, A.: Design, development and management of an information recovery system for an Internet Website : from documentary theory to practice (2003) 0.01
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    Abstract
    A real case study is shown, explaining in a timeline the whole process of design, development and evaluation of a search engine used as a navigational help tool for end users and clients an a content website, e-commerce driven. The nature of the website is a community website, which will determine the core design of the information service. This study will involve several steps, such as information recovery system analysis, comparative analysis of other commercial search engines, service design, functionalities and scope; software selection, design of the project, project management, future service administration and conclusions.
    Type
    a
  18. Voorhees, E.M.: On test collections for adaptive information retrieval (2008) 0.01
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    Abstract
    Traditional Cranfield test collections represent an abstraction of a retrieval task that Sparck Jones calls the "core competency" of retrieval: a task that is necessary, but not sufficient, for user retrieval tasks. The abstraction facilitates research by controlling for (some) sources of variability, thus increasing the power of experiments that compare system effectiveness while reducing their cost. However, even within the highly-abstracted case of the Cranfield paradigm, meta-analysis demonstrates that the user/topic effect is greater than the system effect, so experiments must include a relatively large number of topics to distinguish systems' effectiveness. The evidence further suggests that changing the abstraction slightly to include just a bit more characterization of the user will result in a dramatic loss of power or increase in cost of retrieval experiments. Defining a new, feasible abstraction for supporting adaptive IR research will require winnowing the list of all possible factors that can affect retrieval behavior to a minimum number of essential factors.
    Footnote
    Beitrag in einem Themenheft "Adaptive information retrieval"
    Source
    Information processing and management. 44(2008) no.6, S.1879-1885
    Type
    a
  19. Brown, E.W.; Carmel, D.; Franz, M.; Ittycheriah, A.; Kanungo, T.; Maarek, Y.; McCarley, J.S.; Mack, R.L.; Prager, J.M.; Smith, J.R.; Soffer, A.; Zien, J.Y.; Marwick, A.D.: IBM research activities at TREC (2005) 0.01
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    Source
    TREC: experiment and evaluation in information retrieval. Ed.: E.M. Voorhees, u. D.K. Harman
    Type
    a
  20. Bar-Ilan, J.: Methods for measuring search engine performance over time (2002) 0.01
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    Abstract
    This study introduces methods for evaluating search engine performance over a time period. Several measures are defined, which as a whole describe search engine functionality over time. The necessary setup for such studies is described, and the use of these measures is illustrated through a specific example. The set of measures introduced here may serve as a guideline for the search engines for testing and improving their functionality. We recommend setting up a standard suite of measures for evaluating search engine performance.
    Source
    Journal of the American Society for Information Science and technology. 53(2002) no.4, S.308-319
    Type
    a

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