Search (14 results, page 1 of 1)

  • × theme_ss:"Suchmaschinen"
  • × theme_ss:"Retrievalstudien"
  1. Griesbaum, J.; Rittberger, M.; Bekavac, B.: Deutsche Suchmaschinen im Vergleich : AltaVista.de, Fireball.de, Google.de und Lycos.de (2002) 0.00 
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    Information und Mobilität: Optimierung und Vermeidung von Mobilität durch Information. Proceedings des 8. Internationalen Symposiums für Informationswissenschaft (ISI 2002), 7.-10.10.2002, Regensburg. Hrsg.: Rainer Hammwöhner, Christian Wolff, Christa Womser-Hacker
  2. Agata, T.: ¬A measure for evaluating search engines on the World Wide Web : retrieval test with ESL (Expected Search Length) (1997) 0.00 
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    Source
    Library and information science. 1997, no.37, S.1-11
  3. Landoni, M.; Bell, S.: Information retrieval techniques for evaluating search engines : a critical overview (2000) 0.00 
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    Abstract
    The objective of this paper is to highlight the importance of a scientifically sounded approach to search engine evaluation. Nowadays there is a flourishing literature which describes various attempts at conducting such evaluation by following all sort of approaches, but very often only the final results are published with little, if any, information about the methodology and the procedures adopted. These various experiments have been critically investigated and catalogued according to their scientific foundation by Bell [1] in the attempt to provide a valuable framework for future studies in this area. This paper reconsiders some of Bell's ideas in the light of the crisis of classic evaluation techniques for information retrieval and tries to envisage some form of collaboration between the IR and web communities in order to design a better and more consistent platform for the evaluation of tools for interactive information retrieval.
  4. Serrano Cobos, J.; Quintero Orta, A.: Design, development and management of an information recovery system for an Internet Website : from documentary theory to practice (2003) 0.00 
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    Abstract
    A real case study is shown, explaining in a timeline the whole process of design, development and evaluation of a search engine used as a navigational help tool for end users and clients an a content website, e-commerce driven. The nature of the website is a community website, which will determine the core design of the information service. This study will involve several steps, such as information recovery system analysis, comparative analysis of other commercial search engines, service design, functionalities and scope; software selection, design of the project, project management, future service administration and conclusions.
  5. 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.
    Source
    Journal of the Association for Information Science and Technology. 72(2021) no.2, S.141-155
  6. Dresel, R.; Hörnig, D.; Kaluza, H.; Peter, A.; Roßmann, A.; Sieber, W.: Evaluation deutscher Web-Suchwerkzeuge : Ein vergleichender Retrievaltest (2001) 0.00 
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    Source
    nfd Information - Wissenschaft und Praxis. 52(2001) H.7, S.381-392
  7. Bar-Ilan, J.: Methods for measuring search engine performance over time (2002) 0.00 
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    Source
    Journal of the American Society for Information Science and technology. 53(2002) no.4, S.308-319
  8. Grasso, L.L.; Wahlig, H.: Google und seine Suchparameter : Eine Top 20-Precision Analyse anhand repräsentativ ausgewählter Anfragen (2005) 0.00 
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    Source
    Information - Wissenschaft und Praxis. 56(2005) H.2, S.77-86
  9. Griesbaum, J.: Evaluierung hybrider Suchsysteme im WWW (2000) 0.00 
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    Abstract
    Der Ausgangspunkt dieser Arbeit ist die Suchproblematik im World Wide Web. Suchmaschinen sind einerseits unverzichtbar für erfolgreiches Information Retrieval, andererseits wird ihnen eine mäßige Leistungsfähigkeit vorgeworfen. Das Thema dieser Arbeit ist die Untersuchung der Retrievaleffektivität deutschsprachiger Suchmaschinen. Es soll festgestellt werden, welche Retrievaleffektivität Nutzer derzeit erwarten können. Ein Ansatz, um die Retrievaleffektivität von Suchmaschinen zu erhöhen besteht darin, redaktionell von Menschen erstellte und automatisch generierte Suchergebnisse in einer Trefferliste zu vermengen. Ziel dieser Arbeit ist es, die Retrievaleffektivität solcher hybrider Systeme im Vergleich zu rein roboterbasierten Suchmaschinen zu evaluieren. Zunächst werden hierzu die grundlegenden Problembereiche bei der Evaluation von Retrievalsystemen analysiert. In Anlehnung an die von Tague-Sutcliff vorgeschlagene Methodik wird unter Beachtung der webspezifischen Besonderheiten eine mögliche Vorgehensweise erschlossen. Darauf aufbauend wird das konkrete Setting für die Durchführung der Evaluation erarbeitet und ein Retrievaleffektivitätstest bei den Suchmaschinen Lycos.de, AItaVista.de und QualiGo durchgeführt.
  10. Radev, D.R.; Libner, K.; Fan, W.: Getting answers to natural language questions on the Web (2002) 0.00 
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    Source
    Journal of the American Society for Information Science and technology. 53(2002) no.5, S.359-364
  11. Eastman, C.M.: 30,000 hits may be better than 300 : precision anomalies in Internet searches (2002) 0.00 
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    Source
    Journal of the American Society for Information Science and Technology. 53(2002) no.11, S.879-882
  12. Günther, M.: Vermitteln Suchmaschinen vollständige Bilder aktueller Themen? : Untersuchung der Gewichtung inhaltlicher Aspekte von Suchmaschinenergebnissen in Deutschland und den USA (2016) 0.00 
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    Source
    Young information scientists. 1(2016), S.13-29
  13. Schaer, P.; Mayr, P.; Sünkler, S.; Lewandowski, D.: How relevant is the long tail? : a relevance assessment study on million short (2016) 0.00 
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    Abstract
    Users of web search engines are known to mostly focus on the top ranked results of the search engine result page. While many studies support this well known information seeking pattern only few studies concentrate on the question what users are missing by neglecting lower ranked results. To learn more about the relevance distributions in the so-called long tail we conducted a relevance assessment study with the Million Short long-tail web search engine. While we see a clear difference in the content between the head and the tail of the search engine result list we see no statistical significant differences in the binary relevance judgments and weak significant differences when using graded relevance. The tail contains different but still valuable results. We argue that the long tail can be a rich source for the diversification of web search engine result lists but it needs more evaluation to clearly describe the differences.
  14. Sarigil, E.; Sengor Altingovde, I.; Blanco, R.; Barla Cambazoglu, B.; Ozcan, R.; Ulusoy, Ö.: Characterizing, predicting, and handling web search queries that match very few or no results (2018) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 69(2018) no.2, S.256-270

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