Search (3 results, page 1 of 1)

  • × year_i:[2020 TO 2030}
  • × theme_ss:"Suchmaschinen"
  1. Sundin, O.; Lewandowski, D.; Haider, J.: Whose relevance? : Web search engines as multisided relevance machines (2022) 0.04
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    Abstract
    This opinion piece takes Google's response to the so-called COVID-19 infodemic, as a starting point to argue for the need to consider societal relevance as a complement to other types of relevance. The authors maintain that if information science wants to be a discipline at the forefront of research on relevance, search engines, and their use, then the information science research community needs to address itself to the challenges and conditions that commercial search engines create in. The article concludes with a tentative list of related research topics.
  2. Christensen, A.: Wissenschaftliche Literatur entdecken : was bibliothekarische Discovery-Systeme von der Konkurrenz lernen und was sie ihr zeigen können (2022) 0.03
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    Abstract
    In den letzten Jahren ist das Angebot an Academic Search Engines für die Recherche nach Fachliteratur zu allen Wissenschaftsgebieten stark angewachsen und ergänzt die beliebten kommerziellen Angebote wie Web of Science oder Scopus. Der Artikel zeigt die wesentlichen Unterschiede zwischen bibliothekarischen Discovery-Systemen und Academic Search Engines wie Base, Dimensions oder Open Alex auf und diskutiert Möglichkeiten, wie beide von einander profitieren können. Diese Entwicklungsperspektiven betreffen Aspekte wie die Kontextualisierung von Wissen, die Datenmodellierung, die automatischen Datenanreicherung sowie den Zuschnitt von Suchräumen.
  3. Vegt, A. van der; Zuccon, G.; Koopman, B.: Do better search engines really equate to better clinical decisions? : If not, why not? (2021) 0.02
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    Abstract
    Previous research has found that improved search engine effectiveness-evaluated using a batch-style approach-does not always translate to significant improvements in user task performance; however, these prior studies focused on simple recall and precision-based search tasks. We investigated the same relationship, but for realistic, complex search tasks required in clinical decision making. One hundred and nine clinicians and final year medical students answered 16 clinical questions. Although the search engine did improve answer accuracy by 20 percentage points, there was no significant difference when participants used a more effective, state-of-the-art search engine. We also found that the search engine effectiveness difference, identified in the lab, was diminished by around 70% when the search engines were used with real users. Despite the aid of the search engine, half of the clinical questions were answered incorrectly. We further identified the relative contribution of search engine effectiveness to the overall end task success. We found that the ability to interpret documents correctly was a much more important factor impacting task success. If these findings are representative, information retrieval research may need to reorient its emphasis towards helping users to better understand information, rather than just finding it for them.

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