Search (13 results, page 1 of 1)

  • × theme_ss:"Suchmaschinen"
  • × type_ss:"el"
  1. Dunning, A.: Do we still need search engines? (1999) 0.02
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    Source
    Ariadne. 1999, no.22
  2. Birmingham, J.: Internet search engines (1996) 0.02
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    Date
    10.11.1996 16:36:22
  3. Bladow, N.; Dorey, C.; Frederickson, L.; Grover, P.; Knudtson, Y.; Krishnamurthy, S.; Lazarou, V.: What's the Buzz about? : An empirical examination of Search on Yahoo! (2005) 0.02
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  4. Ding, L.; Finin, T.; Joshi, A.; Peng, Y.; Cost, R.S.; Sachs, J.; Pan, R.; Reddivari, P.; Doshi, V.: Swoogle : a Semantic Web search and metadata engine (2004) 0.02
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  5. Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013) 0.01
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    Date
    17.12.2013 11:02:22
  6. Schaat, S.: Von der automatisierten Manipulation zur Manipulation der Automatisierung (2019) 0.01
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    Date
    19. 2.2019 17:22:00
  7. Search Engines and Beyond : Developing efficient knowledge management systems, April 19-20 1999, Boston, Mass (1999) 0.01
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    Content
    Ramana Rao (Inxight, Palo Alto, CA) 7 ± 2 Insights on achieving Effective Information Access Session One: Updates and a twelve month perspective Danny Sullivan (Search Engine Watch, US / England) Portalization and other search trends Carol Tenopir (University of Tennessee) Search realities faced by end users and professional searchers Session Two: Today's search engines and beyond Daniel Hoogterp (Retrieval Technologies, McLean, VA) Effective presentation and utilization of search techniques Rick Kenny (Fulcrum Technologies, Ontario, Canada) Beyond document clustering: The knowledge impact statement Gary Stock (Ingenius, Kalamazoo, MI) Automated change monitoring Gary Culliss (Direct Hit, Wellesley Hills, MA) User popularity ranked search engines Byron Dom (IBM, CA) Automatically finding the best pages on the World Wide Web (CLEVER) Peter Tomassi (LookSmart, San Francisco, CA) Adding human intellect to search technology Session Three: Panel discussion: Human v automated categorization and editing Ev Brenner (New York, NY)- Chairman James Callan (University of Massachusetts, MA) Marc Krellenstein (Northern Light Technology, Cambridge, MA) Dan Miller (Ask Jeeves, Berkeley, CA) Session Four: Updates and a twelve month perspective Steve Arnold (AIT, Harrods Creek, KY) Review: The leading edge in search and retrieval software Ellen Voorhees (NIST, Gaithersburg, MD) TREC update Session Five: Search engines now and beyond Intelligent Agents John Snyder (Muscat, Cambridge, England) Practical issues behind intelligent agents Text summarization Therese Firmin, (Dept of Defense, Ft George G. Meade, MD) The TIPSTER/SUMMAC evaluation of automatic text summarization systems Cross language searching Elizabeth Liddy (TextWise, Syracuse, NY) A conceptual interlingua approach to cross-language retrieval. Video search and retrieval Armon Amir (IBM, Almaden, CA) CueVideo: Modular system for automatic indexing and browsing of video/audio Speech recognition Michael Witbrock (Lycos, Waltham, MA) Retrieval of spoken documents Visualization James A. Wise (Integral Visuals, Richland, WA) Information visualization in the new millennium: Emerging science or passing fashion? Text mining David Evans (Claritech, Pittsburgh, PA) Text mining - towards decision support
  8. mho: Google erweitert Suchfunktion um Informationsdatenbank (2012) 0.01
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    Content
    "Google hat seine Suchmaschine um eine Datenbank erweitert, die die Suchergebnisse um Fakten zu verschiedensten Objekten und Personen ergänzt. Diese semantische Suchfunktion, die vorerst nur Nutzern in den USA zur Verfügung steht, soll Suchbegriffe inhaltlich erkennen und Zusammenhänge zu anderen Themen herstellen. Damit soll Google noch besser erkennen, wonach die Nutzer suchen und möglichst auch gleich weitere Fragen beantworten. In einem Blogeintrag [http://googleblog.blogspot.de/2012/05/introducing-knowledge-graph-things-not.html] erläutert Google-Manager Amit Singhal die neue Funktion, die unter der Bezeichnung "Knowledge Graph" [http://www.google.com/insidesearch/features/search/knowledge.html] firmiert und in einem Video [http://www.youtube.com/watch?v=mmQl6VGvX-c] vorgestellt wird. Dabei handele es sich um eine große Informationsdatenbank, die derzeit über 500 Millionen Objekte und mehr als 3,5 Milliarden Informationen über die Beziehungen zwischen ihnen enthalte. Darunter fänden sich Sehenswürdigkeiten, berühmte Personen, Städte, Sportmannschaften, Gebäude, Orte, Filme, Himmelsobjekte, Kunstwerke oder Ähnliches. Anhand der Suchanfragen und der Ergebnisse wird die Datenbank immer weiter verbessert, verspricht Google. Dank dieser Neuerung verspricht Google seinen Nutzern drei merkliche Verbesserungen. So könne die Suchmaschine nun besser erkennen, wonach genau gesucht werde, beispielsweise das Gebäude Taj Mahal oder der US-Musiker mit gleichem Namen. Weiterhin könne Google durch den Knowledge Graph wichtige Inhalte besser zusammenfassen, beispielsweise die Lebensdaten einer berühmten Person und ihre Leistungen. Auch bereits getätigte Suchen andere Nutzer könnten künftige Suchergebnisse dadurch beeinflussen. So sei für für Suchende etwa von Interesse, welche Bücher Charles Dickens geschrieben habe. Bei dem Architekten Frank Lloyd Wright sei jedoch weniger die Literatur interessant, als die von ihm gestalteten Gebäude.
  9. Place, E.: Internationale Zusammenarbeit bei Internet Subject Gateways (1999) 0.01
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    Date
    22. 6.2002 19:35:09
  10. Boldi, P.; Santini, M.; Vigna, S.: PageRank as a function of the damping factor (2005) 0.01
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    Date
    16. 1.2016 10:22:28
  11. Baeza-Yates, R.; Boldi, P.; Castillo, C.: Generalizing PageRank : damping functions for linkbased ranking algorithms (2006) 0.01
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    Date
    16. 1.2016 10:22:28
  12. Sander-Beuermann, W.: Schürfrechte im Informationszeitalter : Google hin, Microsoft her v das Internet braucht eine freie Suchkultur (2005) 0.01
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  13. Gillitzer, B.: Yewno (2017) 0.01
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    Date
    22. 2.2017 10:16:49