Search (6 results, page 1 of 1)

  • × theme_ss:"Retrievalalgorithmen"
  • × theme_ss:"Suchmaschinen"
  1. Tober, M.; Hennig, L.; Furch, D.: SEO Ranking-Faktoren und Rang-Korrelationen 2014 : Google Deutschland (2014) 0.05
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    Date
    13. 9.2014 14:45:22
    Type
    r
  2. 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
  3. Kanaeva, Z.: Ranking: Google und CiteSeer (2005) 0.01
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    Date
    20. 3.2005 16:23:22
  4. 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
  5. 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.
  6. Lempel, R.; Moran, S.: SALSA: the stochastic approach for link-structure analysis (2001) 0.01
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