Search (236 results, page 1 of 12)

  • × theme_ss:"Suchmaschinen"
  1. Li, L.; Shang, Y.; Zhang, W.: Improvement of HITS-based algorithms on Web documents 0.08 
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    Content
    Vgl.: http%3A%2F%2Fdelab.csd.auth.gr%2F~dimitris%2Fcourses%2Fir_spring06%2Fpage_rank_computing%2Fp527-li.pdf. Vgl. auch: http://www2002.org/CDROM/refereed/643/.
  2. Mukherjea, S.; Hirata, K.; Hara, Y.: Towards a multimedia World-Wide Web information retrieval engine (1997) 0.07 
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    Date
    1. 8.1996 22:08:06
  3. Großjohann, K.: Gathering-, Harvesting-, Suchmaschinen (1996) 0.06 
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    Date
    7. 2.1996 22:38:41
    Pages
    22 S
  4. Breyer, K.: Kommerz statt Information (2002) 0.04 
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    Date
    9. 5.2002 21:21:22
  5. Park, E.-K.; Ra, D.-Y.; Jang, M.-G.: Techniques for improving web retrieval effectiveness (2005) 0.04 
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  6. Boldi, P.; Santini, M.; Vigna, S.: PageRank as a function of the damping factor (2005) 0.03 
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    Abstract
    PageRank is defined as the stationary state of a Markov chain. The chain is obtained by perturbing the transition matrix induced by a web graph with a damping factor alpha that spreads uniformly part of the rank. The choice of alpha is eminently empirical, and in most cases the original suggestion alpha=0.85 by Brin and Page is still used. Recently, however, the behaviour of PageRank with respect to changes in alpha was discovered to be useful in link-spam detection. Moreover, an analytical justification of the value chosen for alpha is still missing. In this paper, we give the first mathematical analysis of PageRank when alpha changes. In particular, we show that, contrarily to popular belief, for real-world graphs values of alpha close to 1 do not give a more meaningful ranking. Then, we give closed-form formulae for PageRank derivatives of any order, and an extension of the Power Method that approximates them with convergence O(t**k*alpha**t) for the k-th derivative. Finally, we show a tight connection between iterated computation and analytical behaviour by proving that the k-th iteration of the Power Method gives exactly the PageRank value obtained using a Maclaurin polynomial of degree k. The latter result paves the way towards the application of analytical methods to the study of PageRank.
    Date
    16. 1.2016 10:22:28
  7. Khopkar, Y.; Spink, A.; Giles, C.L.; Shah, P.; Debnath, S.: Search engine personalization : An exploratory study (2003) 0.03 
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  8. Rieh, S.Y.; Kim, Y.-M.; Markey, K.: Amount of invested mental effort (AIME) in online searching (2012) 0.03 
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  9. Vaughan, L.; Chen, Y.: Data mining from web search queries : a comparison of Google trends and Baidu index (2015) 0.03 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.1, S.13-22
  10. Williamson, N.J.: Knowledge structures and the Internet : progress and prospects (2006) 0.03 
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    Date
    27.12.2008 15:56:22
    Source
    Knowledge organization for a global learning society: Proceedings of the 9th International ISKO Conference, 4-7 July 2006, Vienna, Austria. Hrsg.: G. Budin, C. Swertz u. K. Mitgutsch
  11. Zhang, D.; Dong, Y.: ¬An effective algorithm to rank Web resources (2000) 0.03 
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  12. Head, M.; Archer, N.; Yuan, Y.: World Wide Web navigation aid (2000) 0.03 
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  13. Patzwaldt, K.: Google Inside (2005) 0.02 
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    Date
    10. 6.2005 17:43:22
    Source
    ¬Die Google-Gesellschaft: Vom digitalen Wandel des Wissens. Hrsg.: K. Lehmann, M. Schetsche
  14. Höfer, W.: Detektive im Web (1999) 0.02 
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    Date
    22. 8.1999 20:22:06
  15. Rensman, J.: Blick ins Getriebe (1999) 0.02 
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    Date
    22. 8.1999 21:22:59
  16. Wu, L.-L.; Chuang, Y.-L.; Chen, P.-Y.: Motivation for using search engines : a two-factor model (2008) 0.02 
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    Footnote
    Vgl.: Wu, L.-L., A. Chuang u. P.-Y. Chen: Correction to Wu, L., Chuang, A., & Chen, P. (2008). Motivation for using search engines: A two factor model. Journal of American Society for Information Science and Technology, 59(11), 1829-1840. In: Journal of the American Society for Information Science and Technology. 61(2010) no.1, S.214-216.
  17. Song, R.; Luo, Z.; Nie, J.-Y.; Yu, Y.; Hon, H.-W.: Identification of ambiguous queries in web search (2009) 0.02 
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  18. Stock, M.; Stock, W.G.: Recherchieren im Internet (2004) 0.02 
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    Date
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  19. Pulido, J.R.V.: Recupracion de la information en Internet : motores y otros agentes des busqueda (1997) 0.02 
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