Search (16 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) 0.00 
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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.
    Type
    a
  2. Kang, X.; Wu, Y.; Ren, W.: Toward action comprehension for searching : mining actionable intents in query entities (2020) 0.00 
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    Abstract
    Understanding search engine users' intents has been a popular study in information retrieval, which directly affects the quality of retrieved information. One of the fundamental problems in this field is to find a connection between the entity in a query and the potential intents of the users, the latter of which would further reveal important information for facilitating the users' future actions. In this article, we present a novel research method for mining the actionable intents for search users, by generating a ranked list of the potentially most informative actions based on a massive pool of action samples. We compare different search strategies and their combinations for retrieving the action pool and develop three criteria for measuring the informativeness of the selected action samples, that is, the significance of an action sample within the pool, the representativeness of an action sample for the other candidate samples, and the diverseness of an action sample with respect to the selected actions. Our experiment, based on the Action Mining (AM) query entity data set from the Actionable Knowledge Graph (AKG) task at NTCIR-13, suggests that the proposed approach is effective in generating an informative and early-satisfying ranking of potential actions for search users.
    Type
    a
  3. Freistetter, F.: Vollkommen logisch (2020) 0.00 
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    Type
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  4. Zeynali-Tazehkandi, M.; Nowkarizi, M.: ¬ A dialectical approach to search engine evaluation (2020) 0.00 
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    Abstract
    Evaluation of information retrieval systems is a fundamental topic in Library and Information Science. The aim of this paper is to connect the system-oriented and the user-oriented approaches to relevant philosophical schools. By reviewing the related literature, it was found that the evaluation of information retrieval systems is successful if it benefits from both system-oriented and user-oriented approaches (composite). The system-oriented approach is rooted in Parmenides' philosophy of stability (immovable) which Plato accepts and attributes to the world of forms; the user-oriented approach is rooted in Heraclitus' flux philosophy (motion) which Plato defers and attributes to the tangible world. Thus, using Plato's theory is a comprehensive approach for recognizing the concept of relevance. The theoretical and philosophical foundations determine the type of research methods and techniques. Therefore, Plato's dialectical method is an appropriate composite method for evaluating information retrieval systems.
    Type
    a
  5. Sa, N.; Yuan, X.(J.): Improving the effectiveness of voice search systems through partial query modification (2022) 0.00 
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    Abstract
    This paper addresses the importance of improving the effectiveness of voice search systems through partial query modification. A user-centered experiment was designed to compare the effectiveness of an experimental system using partial query modification feature to a baseline system in which users could issue complete queries only, with 32 participants each searching on eight different tasks. The results indicate that the participants spent significantly more time preparing the modification but significantly less time speaking the modification by using the experimental system than by using the baseline system. The participants found that the experimental system (a) was more effective, (b) gave them more control, (c) was easier for the search tasks, and (d) saved them time than the baseline system. The results contribute to improving future voice search system design and benefiting the research community in general. System implications and future work were discussed.
    Type
    a
  6. Haring, M.; Rudaev, A.; Lewandowski, D.: Google & Co. : wie die "Search Studies" an der HAW Hamburg unserem Nutzungsverhalten auf den Zahn fühlen: Blickpunkt angewandte Forschung (2022) 0.00 
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  7. Advanced online media use (2023) 0.00 
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    Content
    "1. Use a range of different media 2. Access paywalled media content 3. Use an advertising and tracking blocker 4. Use alternatives to Google Search 5. Use alternatives to YouTube 6. Use alternatives to Facebook and Twitter 7. Caution with Wikipedia 8. Web browser, email, and internet access 9. Access books and scientific papers 10. Access deleted web content"
    Type
    a
  8. Vegt, A. van der; Zuccon, G.; Koopman, B.: Do better search engines really equate to better clinical decisions? : If not, why not? (2021) 0.00 
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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.
    Type
    a
  9. Ogden, J.; Summers, E.; Walker, S.: Know(ing) Infrastructure : the wayback machine as object and instrument of digital research (2023) 0.00 
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    Abstract
    From documenting human rights abuses to studying online advertising, web archives are increasingly positioned as critical resources for a broad range of scholarly Internet research agendas. In this article, we reflect on the motivations and methodological challenges of investigating the world's largest web archive, the Internet Archive's Wayback Machine (IAWM). Using a mixed methods approach, we report on a pilot project centred around documenting the inner workings of 'Save Page Now' (SPN) - an Internet Archive tool that allows users to initiate the creation and storage of 'snapshots' of web resources. By improving our understanding of SPN and its role in shaping the IAWM, this work examines how the public tool is being used to 'save the Web' and highlights the challenges of operationalising a study of the dynamic sociotechnical processes supporting this knowledge infrastructure. Inspired by existing Science and Technology Studies (STS) approaches, the paper charts our development of methodological interventions to support an interdisciplinary investigation of SPN, including: ethnographic methods, 'experimental blackbox tactics', data tracing, modelling and documentary research. We discuss the opportunities and limitations of our methodology when interfacing with issues associated with temporality, scale and visibility, as well as critically engage with our own positionality in the research process (in terms of expertise and access). We conclude with reflections on the implications of digital STS approaches for 'knowing infrastructure', where the use of these infrastructures is unavoidably intertwined with our ability to study the situated and material arrangements of their creation.
    Type
    a
  10. Sander, M.; Cronimund, C.: Google anonym nutzen? : Wie ein Zürcher den Tech-Giganten austrickst (2021) 0.00 
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  11. Meineck, S.: Gesichter-Suchmaschine PimEyes bricht das Schweigen : Neuer Chef (2022) 0.00 
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  12. dpa: ¬Das sind die besten Google-Alternativen (2023) 0.00 
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  13. Christensen, A.: Wissenschaftliche Literatur entdecken : was bibliothekarische Discovery-Systeme von der Konkurrenz lernen und was sie ihr zeigen können (2022) 0.00 
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  14. Leisinger, C.: Sobald die Konkurrenten eine faire Chance haben, wird Google auf einen Schlag 20 Prozent seines Marktanteils verlieren (2020) 0.00 
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  15. Lewandowski, D.: Suchmaschinen (2023) 0.00 
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  16. Option für Metager als Standardsuchmaschine, Suchmaschine nach dem Peer-to-Peer-Prinzip (2021) 0.00 
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    Content
    "Option für Metager als Standardsuchmaschine. Google wurde von der EU verordnet, auf Android-Smartphones bei Neukonfiguration eine Auswahl an Suchmaschinen anzubieten, die als Standardsuchmaschine eingerichtet werden können. Suchmaschinen konnten sich im Rahmen einer Auktion bewerben. Auch wir hatten am Auktionsverfahren teilgenommen, jedoch rein formell mit einem Gebot von null Euro. Nun wurde Google von der EU angewiesen, auf das wettbewerbsverzerrende Auktionsverfahren zu verzichten und alle angemeldeten Suchmaschinen als Option anzubieten. Auf Android ist es nun optional möglich, MetaGer als Standardsuchmaschine für den Bereich D/A/CH auszuwählen. Zwar werden nicht immer alle Suchmaschinen zur Auswahl angezeigt, aber das Zufallsprinzip sorgt immerhin dafür, dass jede Suchmaschine mit einer gewissen Wahrscheinlichkeit in der Liste zu finden ist.
    Type
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