Search (20 results, page 1 of 1)

  • × theme_ss:"Suchmaschinen"
  • × type_ss:"a"
  • × year_i:[2010 TO 2020}
  1. Kaeser, E.: ¬Das postfaktische Zeitalter (2016) 0.05 
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    Content
    "Es gibt Daten, Informationen und Fakten. Wenn man mir eine Zahlenreihe vorsetzt, dann handelt es sich um Daten: unterscheidbare Einheiten, im Fachjargon: Items. Wenn man mir sagt, dass diese Items stündliche Temperaturangaben der Aare im Berner Marzilibad bedeuten, dann verfüge ich über Information - über interpretierte Daten. Wenn man mir sagt, dies seien die gemessenen Aaretemperaturen am 22. August 2016 im Marzili, dann ist das ein Faktum: empirisch geprüfte interpretierte Daten. Dieser Dreischritt - Unterscheiden, Interpretieren, Prüfen - bildet quasi das Bindemittel des Faktischen, «the matter of fact». Wir alle führen den Dreischritt ständig aus und gelangen so zu einem relativ verlässlichen Wissen und Urteilsvermögen betreffend die Dinge des Alltags. Aber wie schon die Kurzcharakterisierung durchblicken lässt, bilden Fakten nicht den Felsengrund der Realität. Sie sind kritikanfällig, sowohl von der Interpretation wie auch von der Prüfung her gesehen. Um bei unserem Beispiel zu bleiben: Es kann durchaus sein, dass man uns zwei unterschiedliche «faktische» Temperaturverläufe der Aare am 22. August 2016 vorsetzt.
  2. Lewandowski, D.; Sünkler, S.: ¬Das Relevance Assessment Tool : eine modulare Software zur Unterstützung bei der Durchführung vielfältiger Studien mit Suchmaschinen (2019) 0.03 
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    Abstract
    In diesem Artikel stellen wir eine Software vor, mit der sich Studien zu Such- und Informationssystemen realisieren lassen. Das Relevance Assessment Tool (RAT) soll umfangreiche Untersuchungen mit Daten von kommerziellen Suchmaschinen unterstützen. Die Software ist modular und webbasiert. Es lassen sich damit automatisiert Daten von Suchmaschinen erfassen. Dazu können Studien mit Fragen und Skalen flexibel gestaltet und die Informationsobjekte anhand der Fragen durch Juroren bewertet werden. Durch die Modularität lassen sich die einzelnen Komponenten für eine Vielzahl von Studien nutzen, die sich auf Web-Inhalte beziehen. So kann die Software auch für qualitative Inhaltsanalysen eingesetzt werden oder durch das automatisierte Scraping eine große Datenbasis an Web-Dokumenten liefern, die sich quantitativ in empirischen Studien analysieren lassen.
  3. Söhler, M.: "Dumm wie Google" war gestern : semantische Suche im Netz (2011) 0.02 
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    Content
    - "Gemeinsames Format für strukturierte Daten" Aber warum sollten Google, Yahoo und Bing plötzlich zusammenarbeiten, wo doch bisher die Konkurrenz das Verhältnis prägte? Stefan Keuchel, Pressesprecher von Google Deutschland, betont, alle beteiligten Unternehmen wollten "ein deutliches Zeichen setzen, um die Qualität der Suche zu verbessern". Man entwickele "ein gemeinsames Format für strukturierte Daten, mit dem Dinge ermöglicht werden, die heute noch nicht möglich sind - Stichwort: semantische Suche". Die Ergebnisse aus Schema.org würden "zeitnah" in die Suchmaschine integriert, "denn einen Zeitplan" gebe es nicht. "Erst mit der Einigung auf eine gemeinsame Sprache können Suchmaschinen einen Mehrwert durch semantische Technologien generieren", antwortet Daniel Bahls auf die Frage nach Gemeinsamkeit und Konkurrenz der Suchmaschinen. Er weist außerdem darauf hin, dass es bereits die semantische Suchmaschine Sig.ma gibt. Geschwindigkeit und Menge der Ergebnisse nach einer Suchanfrage spielen hier keine Rolle. Sig.ma sammelt seine Informationen allein im Bereich des semantischen Webs und listet nach einer Anfrage alles Bekannte strukturiert auf."
  4. Lewandowski, D.: Query understanding (2011) 0.01 
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    Date
    18. 9.2018 18:22:18
  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. Fluhr, C.: Crosslingual access to photo databases (2012) 0.01 
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    Date
    17. 4.2012 14:25:22
  8. Chen, L.-C.: Next generation search engine for the result clustering technology (2012) 0.01 
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    Date
    17. 4.2012 15:22:11
  9. Bouidghaghen, O.; Tamine, L.: Spatio-temporal based personalization for mobile search (2012) 0.01 
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    Date
    20. 4.2012 13:19:22
  10. Lewandowski, D.: ¬Die Macht der Suchmaschinen und ihr Einfluss auf unsere Entscheidungen (2014) 0.01 
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    Date
    22. 9.2014 18:54:11
  11. Huvila, I.: Affective capitalism of knowing and the society of search engine (2016) 0.01 
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    Date
    20. 1.2015 18:30:22
  12. Chaudiron, S.; Ihadjadene, M.: Studying Web search engines from a user perspective : key concepts and main approaches (2012) 0.01 
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    Date
    20. 4.2012 13:22:37
  13. Lewandowski, D.; Spree, U.: Ranking of Wikipedia articles in search engines revisited : fair ranking for reasonable quality? (2011) 0.01 
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    Date
    30. 9.2012 19:27:22
  14. Aloteibi, S.; Sanderson, M.: Analyzing geographic query reformulation : an exploratory study (2014) 0.01 
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    Date
    26. 1.2014 18:48:22
  15. Vaughan, L.; Chen, Y.: Data mining from web search queries : a comparison of Google trends and Baidu index (2015) 0.01 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.1, S.13-22
  16. Alqaraleh, S.; Ramadan, O.; Salamah, M.: Efficient watcher based web crawler design (2015) 0.01 
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    Date
    20. 1.2015 18:30:22
  17. epd: Kaiserslauterer Forscher untersuchen Google-Suche (2017) 0.01 
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    Date
    22. 7.2004 9:42:33
  18. Lewandowski, D.; Sünkler, S.: What does Google recommend when you want to compare insurance offerings? (2019) 0.01 
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    Date
    20. 1.2015 18:30:22
  19. Sachse, J.: ¬The influence of snippet length on user behavior in mobile web search (2019) 0.01 
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    20. 1.2015 18:30:22
  20. Averesch, D.: Googeln ohne Google : Mit alternativen Suchmaschinen gelingt ein neutraler Überblick (2010) 0.01 
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    Date
    3. 5.1997 8:44:22

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