Search (87 results, page 1 of 5)

  • × year_i:[2010 TO 2020}
  • × theme_ss:"Suchmaschinen"
  1. Bilal, D.: Ranking, relevance judgment, and precision of information retrieval on children's queries : evaluation of Google, Yahoo!, Bing, Yahoo! Kids, and ask Kids (2012) 0.02 
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    Abstract
    This study employed benchmarking and intellectual relevance judgment in evaluating Google, Yahoo!, Bing, Yahoo! Kids, and Ask Kids on 30 queries that children formulated to find information for specific tasks. Retrieved hits on given queries were benchmarked to Google's and Yahoo! Kids' top-five ranked hits retrieved. Relevancy of hits was judged on a graded scale; precision was calculated using the precision-at-ten metric (P@10). Yahoo! and Bing produced a similar percentage in hit overlap with Google (nearly 30%), but differed in the ranking of hits. Ask Kids retrieved 11% in hit overlap with Google versus 3% by Yahoo! Kids. The engines retrieved 26 hits across query clusters that overlapped with Yahoo! Kids' top-five ranked hits. Precision (P) that the engines produced across the queries was P = 0.48 for relevant hits, and P = 0.28 for partially relevant hits. Precision by Ask Kids was P = 0.44 for relevant hits versus P = 0.21 by Yahoo! Kids. Bing produced the highest total precision (TP) of relevant hits (TP = 0.86) across the queries, and Yahoo! Kids yielded the lowest (TP = 0.47). Average precision (AP) of relevant hits was AP = 0.56 by leading engines versus AP = 0.29 by small engines. In contrast, average precision of partially relevant hits was AP = 0.83 by small engines versus AP = 0.33 by leading engines. Average precision of relevant hits across the engines was highest on two-word queries and lowest on one-word queries. Google performed best on natural language queries; Bing did the same (P = 0.69) on two-word queries. The findings have implications for search engine ranking algorithms, relevance theory, search engine design, research design, and information literacy.
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  2. Bensman, S.J.: Eugene Garfield, Francis Narin, and PageRank : the theoretical bases of the Google search engine (2013) 0.02 
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    Date
    17.12.2013 11:02:22
    Language
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  3. Souza, J.; Carvalho, A.; Cristo, M.; Moura, E.; Calado, P.; Chirita, P.-A.; Nejdl, W.: Using site-level connections to estimate link confidence (2012) 0.02 
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  4. Schaer, P.; Mayr, P.; Sünkler, S.; Lewandowski, D.: How relevant is the long tail? : a relevance assessment study on million short (2016) 0.02 
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  5. Thelwall, M.: Assessing web search engines : a webometric approach (2011) 0.02 
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    Language
    e
    Source
    Innovations in information retrieval: perspectives for theory and practice. Eds.: A. Foster, u. P. Rafferty
  6. Fluhr, C.: Crosslingual access to photo databases (2012) 0.01 
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    Date
    17. 4.2012 14:25:22
    Language
    e
  7. 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
    Language
    e
  8. 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
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  9. 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
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  10. 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
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  11. 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
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  12. 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
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  13. 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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    Journal of the Association for Information Science and Technology. 66(2015) no.1, S.13-22
  14. 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
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  15. 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
    Language
    e
  16. Sachse, J.: ¬The influence of snippet length on user behavior in mobile web search (2019) 0.01 
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  17. Kaeser, E.: ¬Das postfaktische Zeitalter (2016) 0.01 
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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.
  18. Cornelius, P.; Schneemann, R.; Weisel, L.: SUMA-Kongress 2011 - eine bemerkenswerte Tagung ! (2011) 0.01 
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  19. Gossen, T.: Search engines for children : search user interfaces and information-seeking behaviour (2016) 0.01 
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    Date
    1. 2.2016 18:25:22
    Language
    e
  20. Lewandowski, D.: Query understanding (2011) 0.01 
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    Date
    18. 9.2018 18:22:18

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