Search (37 results, page 1 of 2)

  • × theme_ss:"Retrievalalgorithmen"
  • × year_i:[2000 TO 2010}
  1. MacFarlane, A.; Robertson, S.E.; McCann, J.A.: Parallel computing for passage retrieval (2004) 0.05
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    Date
    20. 1.2007 18:30:22
    Source
    Aslib proceedings. 56(2004) no.4, S.201-211
  2. Losada, D.E.; Barreiro, A.: Emebedding term similarity and inverse document frequency into a logical model of information retrieval (2003) 0.05
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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
  3. 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
  4. 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
  5. 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
  6. 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
  7. Dominich, S.: Mathematical foundations of information retrieval (2001) 0.03
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    Date
    22. 3.2008 12:26:32
    Isbn
    0-7923-6861-4
  8. 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
  9. Daniowicz, C.; Baliski, J.: Document ranking based upon Markov chains (2001) 0.01
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    Source
    Information processing and management. 37(2001) no.4, S.623-637
  10. Kanaeva, Z.: Ranking: Google und CiteSeer (2005) 0.01
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    Date
    20. 3.2005 16:23:22
  11. Fan, W.; Fox, E.A.; Pathak, P.; Wu, H.: ¬The effects of fitness functions an genetic programming-based ranking discovery for Web search (2004) 0.01
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    Date
    31. 5.2004 19:22:06
  12. Furner, J.: ¬A unifying model of document relatedness for hybrid search engines (2003) 0.01
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    Date
    11. 9.2004 17:32:22
  13. Witschel, H.F.: Global term weights in distributed environments (2008) 0.01
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    Date
    1. 8.2008 9:44:22
  14. Klas, C.-P.; Fuhr, N.; Schaefer, A.: Evaluating strategic support for information access in the DAFFODIL system (2004) 0.01
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    Date
    16.11.2008 16:22:48
  15. Mandl, T.: Web- und Multimedia-Dokumente : Neuere Entwicklungen bei der Evaluierung von Information Retrieval Systemen (2003) 0.01
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    Source
    Information - Wissenschaft und Praxis. 54(2003) H.4, S.203-210
  16. Stock, W.G.: On relevance distributions (2006) 0.01
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    Date
    4. 7.2006 14:08:08
  17. Vechtomova, O.; Karamuftuoglu, M.: Lexical cohesion and term proximity in document ranking (2008) 0.01
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    Source
    Information processing and management. 44(2008) no.4, S.1485-1502
  18. Picard, J.; Savoy, J.: Enhancing retrieval with hyperlinks : a general model based on propositional argumentation systems (2003) 0.01
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    Abstract
    Fast, effective, and adaptable techniques are needed to automatically organize and retrieve information an the ever-increasing World Wide Web. In that respect, different strategies have been suggested to take hypertext links into account. For example, hyperlinks have been used to (1) enhance document representation, (2) improve document ranking by propagating document score, (3) provide an indicator of popularity, and (4) find hubs and authorities for a given topic. Although the TREC experiments have not demonstrated the usefulness of hyperlinks for retrieval, the hypertext structure is nevertheless an essential aspect of the Web, and as such, should not be ignored. The development of abstract models of the IR task was a key factor to the improvement of search engines. However, at this time conceptual tools for modeling the hypertext retrieval task are lacking, making it difficult to compare, improve, and reason an the existing techniques. This article proposes a general model for using hyperlinks based an Probabilistic Argumentation Systems, in which each of the above-mentioned techniques can be stated. This model will allow to discover some inconsistencies in the mentioned techniques, and to take a higher level and systematic approach for using hyperlinks for retrieval.
    Source
    Journal of the American Society for Information Science and technology. 54(2003) no.4, S.347-355
  19. Oberhauser, O.; Labner, J.: Relevance Ranking in Online-Katalogen : Informationsstand und Perspektiven (2003) 0.01
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    Source
    Mitteilungen der Vereinigung Österreichischer Bibliothekarinnen und Bibliothekare. 56(2003) H.3/4, S.49-63
  20. Bhogal, J.; Macfarlane, A.; Smith, P.: ¬A review of ontology based query expansion (2007) 0.01
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      0.014902794 = sum of:
        0.014902794 = product of:
          0.029805588 = sum of:
            0.029805588 = weight(_text_:4 in 919) [ClassicSimilarity], result of:
              0.029805588 = score(doc=919,freq=2.0), product of:
                0.14201462 = queryWeight, product of:
                  2.7136984 = idf(docFreq=7967, maxDocs=44218)
                  0.0523325 = queryNorm
                0.2098769 = fieldWeight in 919, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.7136984 = idf(docFreq=7967, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=919)
          0.5 = coord(1/2)
      0.5 = coord(1/2)
    
    Source
    Information processing and management. 43(2007) no.4, S.866-886

Languages

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  • d 6
  • m 1
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Types

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  • m 6
  • s 1
  • x 1
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