Search (151 results, page 1 of 8)

  • × theme_ss:"Retrievalalgorithmen"
  1. Losada, D.E.; Barreiro, A.: Emebedding term similarity and inverse document frequency into a logical model of information retrieval (2003) 0.04
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    Date
    22. 3.2003 19:27:23
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.4, S.285-301
  2. Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014) 0.04
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    Date
    22. 8.2014 17:05:18
    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1939-1943
  3. Baloh, P.; Desouza, K.C.; Hackney, R.: Contextualizing organizational interventions of knowledge management systems : a design science perspectiveA domain analysis (2012) 0.04
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    Abstract
    We address how individuals' (workers) knowledge needs influence the design of knowledge management systems (KMS), enabling knowledge creation and utilization. It is evident that KMS technologies and activities are indiscriminately deployed in most organizations with little regard to the actual context of their adoption. Moreover, it is apparent that the extant literature pertaining to knowledge management projects is frequently deficient in identifying the variety of factors indicative for successful KMS. This presents an obvious business practice and research gap that requires a critical analysis of the necessary intervention that will actually improve how workers can leverage and form organization-wide knowledge. This research involved an extensive review of the literature, a grounded theory methodological approach and rigorous data collection and synthesis through an empirical case analysis (Parsons Brinckerhoff and Samsung). The contribution of this study is the formulation of a model for designing KMS based upon the design science paradigm, which aspires to create artifacts that are interdependent of people and organizations. The essential proposition is that KMS design and implementation must be contextualized in relation to knowledge needs and that these will differ for various organizational settings. The findings present valuable insights and further understanding of the way in which KMS design efforts should be focused.
    Date
    11. 6.2012 14:22:34
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.5, S.948-966
  4. Crestani, F.; Dominich, S.; Lalmas, M.; Rijsbergen, C.J.K. van: Mathematical, logical, and formal methods in information retrieval : an introduction to the special issue (2003) 0.03
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    Date
    22. 3.2003 19:27:36
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.4, S.281-284
  5. Fan, W.; Fox, E.A.; Pathak, P.; Wu, H.: ¬The effects of fitness functions an genetic programming-based ranking discovery for Web search (2004) 0.03
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    Date
    31. 5.2004 19:22:06
    Source
    Journal of the American Society for Information Science and technology. 55(2004) no.7, S.628-636
  6. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.03
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    Date
    16.11.2008 16:22:48
    Series
    Lecture notes in computer science; vol.3232
  7. Campos, L.M. de; Fernández-Luna, J.M.; Huete, J.F.: Implementing relevance feedback in the Bayesian network retrieval model (2003) 0.03
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    Date
    22. 3.2003 19:30:19
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.4, S.302-313
  8. Dominich, S.: Mathematical foundations of information retrieval (2001) 0.03
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    Date
    22. 3.2008 12:26:32
    LCSH
    Computer science / Mathematics
    Subject
    Computer science / Mathematics
  9. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.03
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
  10. Burgin, R.: ¬The retrieval effectiveness of 5 clustering algorithms as a function of indexing exhaustivity (1995) 0.03
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    Date
    22. 2.1996 11:20:06
    Source
    Journal of the American Society for Information Science. 46(1995) no.8, S.562-572
  11. Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003) 0.03
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    Date
    22. 3.2003 19:35:46
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.4, S.321-334
  12. Shiri, A.A.; Revie, C.: Query expansion behavior within a thesaurus-enhanced search environment : a user-centered evaluation (2006) 0.03
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    Date
    22. 7.2006 16:32:43
    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.4, S.462-478
  13. Soulier, L.; Jabeur, L.B.; Tamine, L.; Bahsoun, W.: On ranking relevant entities in heterogeneous networks using a language-based model (2013) 0.03
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    Date
    22. 3.2013 19:34:49
    Source
    Journal of the American Society for Information Science and Technology. 64(2013) no.3, S.500-515
  14. Smeaton, A.F.; Rijsbergen, C.J. van: ¬The retrieval effects of query expansion on a feedback document retrieval system (1983) 0.02
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    Date
    30. 3.2001 13:32:22
  15. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.02
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    Date
    25. 8.2005 17:42:22
  16. Fuhr, N.: Ranking-Experimente mit gewichteter Indexierung (1986) 0.02
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    Date
    14. 6.2015 22:12:44
  17. Fuhr, N.: Rankingexperimente mit gewichteter Indexierung (1986) 0.02
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    14. 6.2015 22:12:56
  18. Rada, R.; Bicknell, E.: Ranking documents with a thesaurus (1989) 0.02
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    Journal of the American Society for Information Science. 40(1989) no.5, S.304-310
  19. Davis, C.H.: Beyond Boole : the next logical step (1995) 0.02
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    Bulletin of the American Society for Information Science. 21(1995), S.17-20
  20. MacFarlane, A.; Robertson, S.E.; McCann, J.A.: Parallel computing for passage retrieval (2004) 0.01
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    Date
    20. 1.2007 18:30:22

Years

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