Search (58 results, page 3 of 3)

  • × theme_ss:"Retrievalalgorithmen"
  • × type_ss:"a"
  1. 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
  2. Witschel, H.F.: Global term weights in distributed environments (2008) 0.01 
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    Date
    1. 8.2008 9:44:22
  3. Campos, L.M. de; Fernández-Luna, J.M.; Huete, J.F.: Implementing relevance feedback in the Bayesian network retrieval model (2003) 0.01 
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    Date
    22. 3.2003 19:30:19
  4. Rada, R.; Barlow, J.; Potharst, J.; Zanstra, P.; Bijstra, D.: Document ranking using an enriched thesaurus (1991) 0.01 
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  5. Evans, R.: Beyond Boolean : relevance ranking, natural language and the new search paradigm (1994) 0.01 
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  6. Green, R.: Topical relevance relationships : 2: an exploratory study and preliminary typology (1995) 0.01 
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  7. Fox, E.; Betrabet, S.; Koushik, M.; Lee, W.: Extended Boolean models (1992) 0.01 
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    Source
    Information retrieval: data structures and algorithms. Ed.: W.B. Frakes u. R. Baeza-Yates
  8. Baeza-Yates, R.; Navarro, G.: Block addressing indices for approximate text retrieval (2000) 0.01 
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  9. Dominich, S.; Skrop, A.: PageRank and interaction information retrieval (2005) 0.01 
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    Abstract
    The PageRank method is used by the Google Web search engine to compute the importance of Web pages. Two different views have been developed for the Interpretation of the PageRank method and values: (a) stochastic (random surfer): the PageRank values can be conceived as the steady-state distribution of a Markov chain, and (b) algebraic: the PageRank values form the eigenvector corresponding to eigenvalue 1 of the Web link matrix. The Interaction Information Retrieval (1**2 R) method is a nonclassical information retrieval paradigm, which represents a connectionist approach based an dynamic systems. In the present paper, a different Interpretation of PageRank is proposed, namely, a dynamic systems viewpoint, by showing that the PageRank method can be formally interpreted as a particular case of the Interaction Information Retrieval method; and thus, the PageRank values may be interpreted as neutral equilibrium points of the Web.
  10. Song, D.; Bruza, P.D.: Towards context sensitive information inference (2003) 0.01 
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    Date
    22. 3.2003 19:35:46
  11. Shiri, A.A.; Revie, C.: Query expansion behavior within a thesaurus-enhanced search environment : a user-centered evaluation (2006) 0.01 
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    Date
    22. 7.2006 16:32:43
  12. Soulier, L.; Jabeur, L.B.; Tamine, L.; Bahsoun, W.: On ranking relevant entities in heterogeneous networks using a language-based model (2013) 0.01 
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    Date
    22. 3.2013 19:34:49
  13. Fuhr, N.: Theorie des Information Retrieval I : Modelle (2004) 0.01 
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    Source
    Grundlagen der praktischen Information und Dokumentation. 5., völlig neu gefaßte Ausgabe. 2 Bde. Hrsg. von R. Kuhlen, Th. Seeger u. D. Strauch. Begründet von Klaus Laisiepen, Ernst Lutterbeck, Karl-Heinrich Meyer-Uhlenried. Bd.1: Handbuch zur Einführung in die Informationswissenschaft und -praxis
  14. Lempel, R.; Moran, S.: SALSA: the stochastic approach for link-structure analysis (2001) 0.01 
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  15. Liu, R.-L.; Huang, Y.-C.: Ranker enhancement for proximity-based ranking of biomedical texts (2011) 0.01 
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  16. Hubert, G.; Pitarch, Y.; Pinel-Sauvagnat, K.; Tournier, R.; Laporte, L.: TournaRank : when retrieval becomes document competition (2018) 0.01 
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  17. González-Ibáñez, R.; Esparza-Villamán, A.; Vargas-Godoy, J.C.; Shah, C.: ¬A comparison of unimodal and multimodal models for implicit detection of relevance in interactive IR (2019) 0.01 
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  18. Khoo, C.S.G.; Wan, K.-W.: ¬A simple relevancy-ranking strategy for an interface to Boolean OPACs (2004) 0.01 
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    Source
    Electronic library. 22(2004) no.2, S.112-120

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