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  • × theme_ss:"Suchmaschinen"
  1. Williamson, N.J.: Knowledge structures and the Internet : progress and prospects (2006) 0.06
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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
  2. Li, L.; Shang, Y.; Zhang, W.: Improvement of HITS-based algorithms on Web documents 0.04
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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/.
  3. Todd, R.J.: From surfing to searching : learning activities with search engines (1998) 0.03
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    Abstract
    Contends that it is important that students learn to be users of the WWW and not simply surfers. Sets out a series of learning activities that might be adapted by teacher librarians to suit the particular curriculum context or grade in order to assist students in developing their critical and evaluative skills in raltion to making effective choices about search engines
  4. Großjohann, K.: Gathering-, Harvesting-, Suchmaschinen (1996) 0.03
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    Date
    7. 2.1996 22:38:41
    Pages
    22 S
  5. Höfer, W.: Detektive im Web (1999) 0.03
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    Date
    22. 8.1999 20:22:06
  6. Rensman, J.: Blick ins Getriebe (1999) 0.03
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    Date
    22. 8.1999 21:22:59
  7. Kucukyilmaz, T.; Cambazoglu, B.B.; Aykanat, C.; Baeza-Yates, R.: ¬A machine learning approach for result caching in web search engines (2017) 0.03
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    Abstract
    A commonly used technique for improving search engine performance is result caching. In result caching, precomputed results (e.g., URLs and snippets of best matching pages) of certain queries are stored in a fast-access storage. The future occurrences of a query whose results are already stored in the cache can be directly served by the result cache, eliminating the need to process the query using costly computing resources. Although other performance metrics are possible, the main performance metric for evaluating the success of a result cache is hit rate. In this work, we present a machine learning approach to improve the hit rate of a result cache by facilitating a large number of features extracted from search engine query logs. We then apply the proposed machine learning approach to static, dynamic, and static-dynamic caching. Compared to the previous methods in the literature, the proposed approach improves the hit rate of the result cache up to 0.66%, which corresponds to 9.60% of the potential room for improvement.
  8. Stock, M.; Stock, W.G.: Recherchieren im Internet (2004) 0.03
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    Date
    27.11.2005 18:04:22
  9. MacLeod, R.: Promoting a subject gateway : a case study from EEVL (Edinburgh Engineering Virtual Library) (2000) 0.02
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    Date
    22. 6.2002 19:40:22
  10. Vidmar, D.J.: Darwin on the Web : the evolution of search tools (1999) 0.02
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    Source
    Computers in libraries. 19(1999) no.5, S.22-28
  11. 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
  12. ap: Suchmaschinen in neuem Gewand : Metaspinner kennt 600 Millionen Seiten (1999) 0.02
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    Date
    3. 5.1997 8:44:22
  13. Dunning, A.: Do we still need search engines? (1999) 0.02
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    Source
    Ariadne. 1999, no.22
  14. Bawden, D.: Google and the universe of knowledge (2008) 0.02
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    Date
    7. 6.2008 16:22:20
  15. Williamson, N.J.: Knowledge structures and the Internet : progress and prospects (2007) 0.02
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    Content
    Vgl. auch: http://catalogingandclassificationquarterly.com/ - Auch als Beitrag in: Knowledge organization for a globale learning society (ISKO-9)
  16. Shneiderman, B.; Byrd, D.; Croft, W.B.: Clarifying search : a user-interface framework for text searches (1997) 0.02
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    Abstract
    Current user interfaces for textual database searching leave much to be desired: individually, they are often confusing, and as a group, they are seriously inconsistent. We propose a four- phase framework for user-interface design: the framework provides common structure and terminology for searching while preserving the distinct features of individual collections and search mechanisms. Users will benefit from faster learning, increased comprehension, and better control, leading to more effective searches and higher satisfaction.
  17. Auf der Suche nach Suchmaschinen (1996) 0.02
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    Source
    Cogito. 12(1996) H.5, S.19-22
  18. Birmingham, J.: Internet search engines (1996) 0.02
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    Date
    10.11.1996 16:36:22
  19. Bager, J.: Weniger ist mehr : Internet-Suchmaschinen richtig einsetzen (1998) 0.02
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    Date
    29.12.1998 11:22:00
  20. Lob, S.: Per Mausklick auf die neusten Nachrichten : Internet-Suchmaschinen liefern Presse-Überblicke und stellen persönliche Zeitungen zusammen (1998) 0.02
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    Date
    29.12.1998 11:22:25

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