Search (13 results, page 1 of 1)

  • × author_ss:"Lewandowski, D."
  • × theme_ss:"Suchmaschinen"
  • × year_i:[2010 TO 2020}
  1. Lewandowski, D.; Krewinkel, A.; Gleissner, M.; Osterode, D.; Tolg, B.; Holle, M.; Sünkler, S.: Entwicklung und Anwendung einer Software zur automatisierten Kontrolle des Lebensmittelmarktes im Internet mit informationswissenschaftlichen Methoden (2019) 0.04 
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    Abstract
    In diesem Artikel präsentieren wir die Durchführung und die Ergebnisse eines interdisziplinären Forschungsprojekts zum Thema automatisierte Lebensmittelkontrolle im Web. Es wurden Kompetenzen aus den Disziplinen Lebensmittelwissenschaft, Rechtswissenschaft, Informationswissenschaft und Informatik dazu genutzt, ein detailliertes Konzept und einen Software-Prototypen zu entwickeln, um das Internet nach Produktangeboten zu durchsuchen, die gegen das Lebensmittelrecht verstoßen. Dabei wird deutlich, wie ein solcher Anwendungsfall von den Methoden der Information-Retrieval-Evaluierung profitiert, und wie sich mit relativ geringem Aufwand eine flexible Software programmieren lässt, die auch für eine Vielzahl anderer Fragestellungen einsetzbar ist. Die Ergebnisse des Projekts zeigen, wie komplexe Arbeitsprozesse einer Behörde mit Hilfe der Methoden von Retrieval-Tests und gängigen Verfahren aus dem maschinellen Lernen effektiv und effizient unterstützt werden können.
  2. Lewandowski, D.: ¬Die Macht der Suchmaschinen und ihr Einfluss auf unsere Entscheidungen (2014) 0.03 
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    Abstract
    Wenn man die Recherche in Suchmaschinen als Vorbereitung einer Entscheidung betrachtet, kommt diesen Suchwerkzeugen aufgrund der Masse der an sie ge­stellten Anfragen eine nicht zu unterschätzende Bedeutung zu. Macht haben Suchmaschinen vor allem dadurch, dass sie entscheiden, was ein Nutzer zu seiner Suchanfrage zu sehen bekommt, verstärkt durch die ­Entscheidung, an welcher Stelle und in welcher Darstellungsform die Ergebnisse angezeigt werden. Im Suchprozess gibt es zahlreiche Stellen, an denen das Design der Suchmaschine die Entscheidung des Nutzers für oder gegen bestimmte Ergebnisse beeinflusst. Zusammen mit der externen Beeinflussung der Suchergebnisse durch sog. Suchmaschinenoptimierung ergibt sich eine Steuerung der Nutzer hin zu bestimmten Ergebnissen und ­Ergebnisformen. Der Artikel zeigt, wo Suchmaschinen Einfluss auf unsere Entscheidungsvorbereitung bzw. Entscheidungsfindung nehmen, an welchen Punkten dem durch einen bewussteren Umgang mit den Suchmaschinen entgegengewirkt werden kann, aber auch wo die Grenzen der eigenen Entscheidungsmöglichkeiten liegen.
    Date
    22. 9.2014 18:54:11
  3. Lewandowski, D.; Spree, U.: Ranking of Wikipedia articles in search engines revisited : fair ranking for reasonable quality? (2011) 0.01 
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    Abstract
    This paper aims to review the fiercely discussed question of whether the ranking of Wikipedia articles in search engines is justified by the quality of the articles. After an overview of current research on information quality in Wikipedia, a summary of the extended discussion on the quality of encyclopedic entries in general is given. On this basis, a heuristic method for evaluating Wikipedia entries is developed and applied to Wikipedia articles that scored highly in a search engine retrieval effectiveness test and compared with the relevance judgment of jurors. In all search engines tested, Wikipedia results are unanimously judged better by the jurors than other results on the corresponding results position. Relevance judgments often roughly correspond with the results from the heuristic evaluation. Cases in which high relevance judgments are not in accordance with the comparatively low score from the heuristic evaluation are interpreted as an indicator of a high degree of trust in Wikipedia. One of the systemic shortcomings of Wikipedia lies in its necessarily incoherent user model. A further tuning of the suggested criteria catalog, for instance, the different weighing of the supplied criteria, could serve as a starting point for a user model differentiated evaluation of Wikipedia articles. Approved methods of quality evaluation of reference works are applied to Wikipedia articles and integrated with the question of search engine evaluation.
    Date
    30. 9.2012 19:27:22
  4. Lewandowski, D.: Suchmaschinen verstehen (2015) 0.01 
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    Abstract
    Das Buch betrachtet das Thema Suchmaschinen ausgehend von der täglichen Recherche und führt in die technischen Grundlagen, in Recherchetechniken sowie die gesellschaftlichen und wirtschaftlichen Bedingungen der Recherche im Web ein. Suchmaschinen sind heute die wichtigsten Werkzeuge, um an Informationen zu gelangen. Wir verwenden Suchmaschinen täglich, meist ohne weiter darüber nachzudenken. Doch wie funktionieren diese Suchwerkzeuge eigentlich genau? Neben einer ausführlichen Darstellung der in den bekannten Suchmaschinen verwendeten Rankingverfahren wird auch ausführlich auf das Nutzerverhalten eingegangen, das wiederum die Ergebnisdarstellung prägt. Dazu kommen grundlegende Betrachtungen des Suchmaschinenmarkts, der Bedeutung der Suchmaschinenoptimierung und der Rolle der Suchmaschinen als technische Informationsvermittler. Nicht zuletzt wird auch die Seite der Recherche betrachtet und gezeigt, wie man mit den bekannten Suchmaschinen effizient recherchieren kann. Das Buch verhilft allen, die mit Suchmaschinen recherchieren oder sich beruflich mit der Optimierung, Aufbereitung und Sichtbarmachung von Inhalten beschäftigen, zu einem umfassenden Verständnis der Ansätze, Stärken und Schwächen verschiedener Suchmaschinen und der ihnen zugrunde liegenden Technologien.
  5. Lewandowski, D.: Query understanding (2011) 0.01 
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    Date
    18. 9.2018 18:22:18
  6. Lewandowski, D.: ¬A framework for evaluating the retrieval effectiveness of search engines (2012) 0.01 
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    Abstract
    This chapter presents a theoretical framework for evaluating next generation search engines. The author focuses on search engines whose results presentation is enriched with additional information and does not merely present the usual list of "10 blue links," that is, of ten links to results, accompanied by a short description. While Web search is used as an example here, the framework can easily be applied to search engines in any other area. The framework not only addresses the results presentation, but also takes into account an extension of the general design of retrieval effectiveness tests. The chapter examines the ways in which this design might influence the results of such studies and how a reliable test is best designed.
    Source
    Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
  7. Lewandowski, D.: Evaluating the retrieval effectiveness of web search engines using a representative query sample (2015) 0.00 
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    Abstract
    Search engine retrieval effectiveness studies are usually small scale, using only limited query samples. Furthermore, queries are selected by the researchers. We address these issues by taking a random representative sample of 1,000 informational and 1,000 navigational queries from a major German search engine and comparing Google's and Bing's results based on this sample. Jurors were found through crowdsourcing, and data were collected using specialized software, the Relevance Assessment Tool (RAT). We found that although Google outperforms Bing in both query types, the difference in the performance for informational queries was rather low. However, for navigational queries, Google found the correct answer in 95.3% of cases, whereas Bing only found the correct answer 76.6% of the time. We conclude that search engine performance on navigational queries is of great importance, because users in this case can clearly identify queries that have returned correct results. So, performance on this query type may contribute to explaining user satisfaction with search engines.
  8. Lewandowski, D.; Sünkler, S.; Kerkmann, F.: Are ads on Google search engine results pages labeled clearly enough? : the influence of knowledge on search ads on users' selection behaviour (2017) 0.00 
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    Abstract
    In an online experiment using a representative sample of the German online population (n = 1.000), we compare users' selection behaviour on two versions of the same Google search engine results page (SERP), one showing advertisements and organic results, the other showing organic results only. Selection behaviour is analyzed in relation to users' knowledge on Google's business model, on SERP design, and on these users' actual performance in marking advertisements on SERPs correctly. We find that users who were not able to mark ads correctly selected ads significantly more often. This leads to the conclusion that ads need to be labeled more clearly, and that there is a need for more information literacy in search engine users.
  9. Lewandowski, D.: ¬The retrieval effectiveness of search engines on navigational queries (2011) 0.00 
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    Abstract
    Purpose - The purpose of this paper is to test major web search engines on their performance on navigational queries, i.e. searches for homepages. Design/methodology/approach - In total, 100 user queries are posed to six search engines (Google, Yahoo!, MSN, Ask, Seekport, and Exalead). Users described the desired pages, and the results position of these was recorded. Measured success and mean reciprocal rank are calculated. Findings - The performance of the major search engines Google, Yahoo!, and MSN was found to be the best, with around 90 per cent of queries answered correctly. Ask and Exalead performed worse but received good scores as well. Research limitations/implications - All queries were in German, and the German-language interfaces of the search engines were used. Therefore, the results are only valid for German queries. Practical implications - When designing a search engine to compete with the major search engines, care should be taken on the performance on navigational queries. Users can be influenced easily in their quality ratings of search engines based on this performance. Originality/value - This study systematically compares the major search engines on navigational queries and compares the findings with studies on the retrieval effectiveness of the engines on informational queries.
  10. Lewandowski, D.; Sünkler, S.: What does Google recommend when you want to compare insurance offerings? (2019) 0.00 
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    Date
    20. 1.2015 18:30:22
  11. Lewandowski, D.: Suchmaschinen verstehen (2018) 0.00 
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    Abstract
    Suchmaschinen sind heute die wichtigsten Werkzeuge, um an Informationen zu gelangen. Wir verwenden Suchmaschinen täglich, meist ohne weiter darüber nachzudenken. Doch wie funktionieren diese Suchwerkzeuge eigentlich genau? Das Buch betrachtet Suchmaschinen aus vier Perspektiven: Technik, Nutzung, Recherche und gesellschaftliche Bedeutung. Es bietet eine klar strukturierte und verständliche Einführung in die Thematik. Zahlreiche Abbildungen erlauben eine schnelle Erfassung des Stoffs. Neben einer ausführlichen Darstellung der in den bekannten Suchmaschinen verwendeten Rankingverfahren wird auch ausführlich auf das Nutzerverhalten eingegangen, das wiederum die Ergebnisdarstellung prägt. Dazu kommen grundlegende Betrachtungen des Suchmaschinenmarktes, der Bedeutung der Suchmaschinenoptimierung und der Rolle der Suchmaschinen als technische Informationsvermittler. Das Buch richtet sich an alle, die mit Suchmaschinen zu tun haben und ein umfassendes Verständnis dieser Suchwerkzeuge erlangen wollen, u.a. Suchmaschinenoptimierer, Entwickler, Informationswissenschaftler, Bibliothekare, Rechercheure in Wissenschaft und Praxis sowie Online-Marketing-Verantwortliche. Für die zweite Auflage wurde der Text vollständig überarbeitet. Neben einem neuen Kapitel zur Suchmaschinenwerbung wurden zahlreiche Abschnitte zu neu aufgekommenen Themen hinzugefügt. Alle Statistiken und Quellen wurden auf den neuesten Stand gebracht.
  12. Lewandowski, D.; Sünkler, S.; Hanisch, F.: Anzeigenkennzeichnung auf Suchergebnisseiten : Empirische Ergebnisse und Implikationen für die Forschung (2019) 0.00 
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    Abstract
    In diesem Aufsatz stellen wir eine repräsentative Multimethodenstudie (bestehend aus Umfrage, aufgabenbasierter Nutzerstudie und OnlineExperiment) zum Wissen und Verhalten der deutschen Internetnutzer bezüglich der Anzeigen auf Google-Suchergebnisseiten vor. Die Ergebnisse zeigen, dass die überwiegende Mehrzahl der Nutzenden nicht hinreichend in der Lage ist, Werbung von organischen Ergebnissen zu unterscheiden. Die aufgabenbasierte Studie zeigt, dass lediglich 1,3 Prozent der Teilnehmenden alle Anzeigen und organischen Ergebnisse richtig markieren konnten. 9,6 Prozent haben ausschließlich korrekte Markierungen vorgenommen, dabei aber keine Vollständigkeit erreicht. Aus den Ergebnissen der Umfrage geht hervor, dass es viele Unklarheiten gibt über das Geschäftsmodell von Google und die Art und Weise, wie Suchmaschinenwerbung funktioniert. Die Ergebnisse des Online-Experiments zeigen, dass Nutzende, die die Unterscheidung zwischen Anzeigen und organischen Ergebnissen nicht verstehen, etwa doppelt so häufig auf Anzeigen klicken wie diejenigen, die diese Unterscheidung verstehen. Implikationen für die Forschung ergeben sich in den Bereichen Wiederholungsstudien bzw. Monitoring der Anzeigendarstellung, vertiefende Laborstudien, Modelle des Informationsverhaltens, Informationskompetenz und Entwicklung fairer Suchmaschinen.
  13. Lewandowski, D.; Drechsler, J.; Mach, S. von: Deriving query intents from web search engine queries (2012) 0.00 
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    Abstract
    The purpose of this article is to test the reliability of query intents derived from queries, either by the user who entered the query or by another juror. We report the findings of three studies. First, we conducted a large-scale classification study (~50,000 queries) using a crowdsourcing approach. Next, we used clickthrough data from a search engine log and validated the judgments given by the jurors from the crowdsourcing study. Finally, we conducted an online survey on a commercial search engine's portal. Because we used the same queries for all three studies, we also were able to compare the results and the effectiveness of the different approaches. We found that neither the crowdsourcing approach, using jurors who classified queries originating from other users, nor the questionnaire approach, using searchers who were asked about their own query that they just entered into a Web search engine, led to satisfying results. This leads us to conclude that there was little understanding of the classification tasks, even though both groups of jurors were given detailed instructions. Although we used manual classification, our research also has important implications for automatic classification. We must question the success of approaches using automatic classification and comparing its performance to a baseline from human jurors.

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