Search (270 results, page 1 of 14)

  • × theme_ss:"Suchmaschinen"
  1. Rensman, J.: Blick ins Getriebe (1999) 0.10
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    Date
    22. 8.1999 21:22:59
  2. Back, J.: ¬An evaluation of relevancy ranking techniques used by Internet search engines (2000) 0.09
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    Date
    25. 8.2005 17:42:22
  3. Birmingham, J.: Internet search engines (1996) 0.08
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    Date
    10.11.1996 16:36:22
  4. Bager, J.: Weniger ist mehr : Internet-Suchmaschinen richtig einsetzen (1998) 0.08
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    Date
    29.12.1998 11:22:00
  5. Wätjen, H.-J.: Mensch oder Maschine? : Auswahl und Erschließung vonm Informationsressourcen im Internet (1996) 0.06
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    Date
    2. 2.1996 15:40:22
  6. Ding, Y.; Yan, E.; Frazho, A.; Caverlee, J.: PageRank for ranking authors in co-citation networks (2009) 0.06
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    Abstract
    This paper studies how varied damping factors in the PageRank algorithm influence the ranking of authors and proposes weighted PageRank algorithms. We selected the 108 most highly cited authors in the information retrieval (IR) area from the 1970s to 2008 to form the author co-citation network. We calculated the ranks of these 108 authors based on PageRank with the damping factor ranging from 0.05 to 0.95. In order to test the relationship between different measures, we compared PageRank and weighted PageRank results with the citation ranking, h-index, and centrality measures. We found that in our author co-citation network, citation rank is highly correlated with PageRank with different damping factors and also with different weighted PageRank algorithms; citation rank and PageRank are not significantly correlated with centrality measures; and h-index rank does not significantly correlate with centrality measures but does significantly correlate with other measures. The key factors that have impact on the PageRank of authors in the author co-citation network are being co-cited with important authors.
  7. Lewandowski, D.; Sünkler, S.: What does Google recommend when you want to compare insurance offerings? (2019) 0.05
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    Abstract
    Purpose The purpose of this paper is to describe a new method to improve the analysis of search engine results by considering the provider level as well as the domain level. This approach is tested by conducting a study using queries on the topic of insurance comparisons. Design/methodology/approach The authors conducted an empirical study that analyses the results of search queries aimed at comparing insurance companies. The authors used a self-developed software system that automatically queries commercial search engines and automatically extracts the content of the returned result pages for further data analysis. The data analysis was carried out using the KNIME Analytics Platform. Findings Google's top search results are served by only a few providers that frequently appear in these results. The authors show that some providers operate several domains on the same topic and that these domains appear for the same queries in the result lists. Research limitations/implications The authors demonstrate the feasibility of this approach and draw conclusions for further investigations from the empirical study. However, the study is a limited use case based on a limited number of search queries. Originality/value The proposed method allows large-scale analysis of the composition of the top results from commercial search engines. It allows using valid empirical data to determine what users actually see on the search engine result pages.
    Date
    20. 1.2015 18:30:22
  8. Nicholson, S.; Sierra, T.; Eseryel, U.Y.; Park, J.-H.; Barkow, P.; Pozo, E.J.; Ward, J.: How much of it is real? : analysis of paid placement in Web search engine results (2006) 0.05
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    Date
    22. 7.2006 16:32:57
  9. Chaudiron, S.; Ihadjadene, M.: Studying Web search engines from a user perspective : key concepts and main approaches (2012) 0.04
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    Abstract
    This chapter shows that the wider use of Web search engines, reconsidering the theoretical and methodological frameworks to grasp new information practices. Beginning with an overview of the recent challenges implied by the dynamic nature of the Web, this chapter then traces the information behavior related concepts in order to present the different approaches from the user perspective. The authors pay special attention to the concept of "information practice" and other related concepts such as "use", "activity", and "behavior" largely used in the literature but not always strictly defined. The authors provide an overview of user-oriented studies that are meaningful to understand the different contexts of use of electronic information access systems, focusing on five approaches: the system-oriented approaches, the theories of information seeking, the cognitive and psychological approaches, the management science approaches, and the marketing approaches. Future directions of work are then shaped, including social searching and the ethical, cultural, and political dimensions of Web search engines. The authors conclude considering the importance of Critical theory to better understand the role of Web Search engines in our modern society.
    Date
    20. 4.2012 13:22:37
  10. 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.
  11. Bouidghaghen, O.; Tamine, L.: Spatio-temporal based personalization for mobile search (2012) 0.04
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    Abstract
    The explosion of the information available on the Internet has made traditional information retrieval systems, characterized by one size fits all approaches, less effective. Indeed, users are overwhelmed by the information delivered by such systems in response to their queries, particularly when the latter are ambiguous. In order to tackle this problem, the state-of-the-art reveals that there is a growing interest towards contextual information retrieval (CIR) which relies on various sources of evidence issued from the user's search background and environment, in order to improve the retrieval accuracy. This chapter focuses on mobile context, highlights challenges they present for IR, and gives an overview of CIR approaches applied in this environment. Then, the authors present an approach to personalize search results for mobile users by exploiting both cognitive and spatio-temporal contexts. The experimental evaluation undertaken in front of Yahoo search shows that the approach improves the quality of top search result lists and enhances search result precision.
    Date
    20. 4.2012 13:19:22
  12. Large, A.; Beheshti, J.; Rahman, T.: Design criteria for children's Web portals : the users speak out (2002) 0.04
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    Date
    2. 6.2005 10:34:22
  13. Furner, J.: ¬A unifying model of document relatedness for hybrid search engines (2003) 0.04
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    Date
    11. 9.2004 17:32:22
  14. Sachse, J.: ¬The influence of snippet length on user behavior in mobile web search (2019) 0.03
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    Date
    20. 1.2015 18:30:22
  15. Li, L.; Shang, Y.; Zhang, W.: Improvement of HITS-based algorithms on Web documents 0.03
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    Content
    Vgl.: http%3A%2F%2Fdelab.csd.auth.gr%2F~dimitris%2Fcourses%2Fir_spring06%2Fpage_rank_computing%2Fp527-li.pdf. Vgl. auch: http://www2002.org/CDROM/refereed/643/.
  16. Großjohann, K.: Gathering-, Harvesting-, Suchmaschinen (1996) 0.03
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    Date
    7. 2.1996 22:38:41
    Pages
    22 S
  17. Höfer, W.: Detektive im Web (1999) 0.03
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    Date
    22. 8.1999 20:22:06
  18. Souza, J.; Carvalho, A.; Cristo, M.; Moura, E.; Calado, P.; Chirita, P.-A.; Nejdl, W.: Using site-level connections to estimate link confidence (2012) 0.03
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    Abstract
    Search engines are essential tools for web users today. They rely on a large number of features to compute the rank of search results for each given query. The estimated reputation of pages is among the effective features available for search engine designers, probably being adopted by most current commercial search engines. Page reputation is estimated by analyzing the linkage relationships between pages. This information is used by link analysis algorithms as a query-independent feature, to be taken into account when computing the rank of the results. Unfortunately, several types of links found on the web may damage the estimated page reputation and thus cause a negative effect on the quality of search results. This work studies alternatives to reduce the negative impact of such noisy links. More specifically, the authors propose and evaluate new methods that deal with noisy links, considering scenarios where the reputation of pages is computed using the PageRank algorithm. They show, through experiments with real web content, that their methods achieve significant improvements when compared to previous solutions proposed in the literature.
  19. Unkel, J.; Haas, A.: ¬The effects of credibility cues on the selection of search engine results (2017) 0.03
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    Footnote
    This research was supported by the LMUexcellent Junior Researcher Fund. The authors would like to thank Nora Denner, Lena Storck, and especially Ramona Berger for their assistance with experiment supervision and coding, and the reviewers for their valuable suggestions.
  20. Stock, M.; Stock, W.G.: Recherchieren im Internet (2004) 0.03
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    Date
    27.11.2005 18:04:22

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