Search (36 results, page 1 of 2)

  • × author_ss:"Lewandowski, D."
  1. Lewandowski, D.; Spree, U.: Ranking of Wikipedia articles in search engines revisited : fair ranking for reasonable quality? (2011) 0.06 
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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
    Source
    Journal of the American Society for Information Science and Technology. 62(2011) no.1, S.117-132
  2. Lewandowski, D.; Kerkmann, F.; Rümmele, S.; Sünkler, S.: ¬An empirical investigation on search engine ad disclosure (2018) 0.04 
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    Abstract
    This representative study of German search engine users (N?=?1,000) focuses on the ability of users to distinguish between organic results and advertisements on Google results pages. We combine questions about Google's business with task-based studies in which users were asked to distinguish between ads and organic results in screenshots of results pages. We find that only a small percentage of users can reliably distinguish between ads and organic results, and that user knowledge of Google's business model is very limited. We conclude that ads are insufficiently labelled as such, and that many users may click on ads assuming that they are selecting organic results.
    Source
    Journal of the Association for Information Science and Technology. 69(2018) no.3, S.420-437
  3. Sundin, O.; Lewandowski, D.; Haider, J.: Whose relevance? : Web search engines as multisided relevance machines (2022) 0.03 
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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.
    Source
    Journal of the Association for Information Science and Technology. 73(2022) no.5, S.637-642
  4. Lewandowski, D.; Sünkler, S.: What does Google recommend when you want to compare insurance offerings? (2019) 0.03 
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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
    Footnote
    Beitrag in einem Special Issue: Information Science in the German-speaking Countries
    Source
    Aslib journal of information management. 71(2019) no.3, S.310-324
  5. Lewandowski, D.: Evaluating the retrieval effectiveness of web search engines using a representative query sample (2015) 0.03 
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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.
    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.9, S.1763-1775
  6. Lewandowski, D.; Haustein, S.: What does the German-language information science community cite? (2015) 0.02 
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    Source
    Re:inventing information science in the networked society: Proceedings of the 14th International Symposium on Information Science, Zadar/Croatia, 19th-21st May 2015. Eds.: F. Pehar, C. Schloegl u. C. Wolff
  7. 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) 0.02 
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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.
    Source
    Everything changes, everything stays the same? - Understanding information spaces : Proceedings of the 15th International Symposium of Information Science (ISI 2017), Berlin/Germany, 13th - 15th March 2017. Eds.: M. Gäde, V. Trkulja u. V. Petras
  8. Lewandowski, D.; Drechsler, J.; Mach, S. von: Deriving query intents from web search engine queries (2012) 0.02 
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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.
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.9, S.1773-1788
  9. Behnert, C.; Lewandowski, D.: ¬A framework for designing retrieval effectiveness studies of library information systems using human relevance assessments (2017) 0.02 
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    Abstract
    Purpose This paper demonstrates how to apply traditional information retrieval evaluation methods based on standards from the Text REtrieval Conference (TREC) and web search evaluation to all types of modern library information systems including online public access catalogs, discovery systems, and digital libraries that provide web search features to gather information from heterogeneous sources. Design/methodology/approach We apply conventional procedures from information retrieval evaluation to the library information system context considering the specific characteristics of modern library materials. Findings We introduce a framework consisting of five parts: (1) search queries, (2) search results, (3) assessors, (4) testing, and (5) data analysis. We show how to deal with comparability problems resulting from diverse document types, e.g., electronic articles vs. printed monographs and what issues need to be considered for retrieval tests in the library context. Practical implications The framework can be used as a guideline for conducting retrieval effectiveness studies in the library context. Originality/value Although a considerable amount of research has been done on information retrieval evaluation, and standards for conducting retrieval effectiveness studies do exist, to our knowledge this is the first attempt to provide a systematic framework for evaluating the retrieval effectiveness of twenty-first-century library information systems. We demonstrate which issues must be considered and what decisions must be made by researchers prior to a retrieval test.
  10. Lewandowski, D.: Abfragesprachen und erweiterte Funktionen von WWW-Suchmaschinen (2004) 0.02 
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    Date
    28.11.2004 13:11:22
    Source
    Information - Wissenschaft und Praxis. 55(2004) H.2, S.97-102
  11. Lewandowski, D.; Mayr, P.: Exploring the academic invisible Web (2006) 0.01 
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    Abstract
    Purpose: To provide a critical review of Bergman's 2001 study on the Deep Web. In addition, we bring a new concept into the discussion, the Academic Invisible Web (AIW). We define the Academic Invisible Web as consisting of all databases and collections relevant to academia but not searchable by the general-purpose internet search engines. Indexing this part of the Invisible Web is central to scien-tific search engines. We provide an overview of approaches followed thus far. Design/methodology/approach: Discussion of measures and calculations, estima-tion based on informetric laws. Literature review on approaches for uncovering information from the Invisible Web. Findings: Bergman's size estimate of the Invisible Web is highly questionable. We demonstrate some major errors in the conceptual design of the Bergman paper. A new (raw) size estimate is given. Research limitations/implications: The precision of our estimate is limited due to a small sample size and lack of reliable data. Practical implications: We can show that no single library alone will be able to index the Academic Invisible Web. We suggest collaboration to accomplish this task. Originality/value: Provides library managers and those interested in developing academic search engines with data on the size and attributes of the Academic In-visible Web.
  12. Lewandowski, D.; Mayr, P.: Exploring the academic invisible Web (2006) 0.01 
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    Abstract
    Purpose: To provide a critical review of Bergman's 2001 study on the deep web. In addition, we bring a new concept into the discussion, the academic invisible web (AIW). We define the academic invisible web as consisting of all databases and collections relevant to academia but not searchable by the general-purpose internet search engines. Indexing this part of the invisible web is central to scientific search engines. We provide an overview of approaches followed thus far. Design/methodology/approach: Discussion of measures and calculations, estimation based on informetric laws. Literature review on approaches for uncovering information from the invisible web. Findings: Bergman's size estimate of the invisible web is highly questionable. We demonstrate some major errors in the conceptual design of the Bergman paper. A new (raw) size estimate is given. Research limitations/implications: The precision of our estimate is limited due to a small sample size and lack of reliable data. Practical implications: We can show that no single library alone will be able to index the academic invisible web. We suggest collaboration to accomplish this task. Originality/value: Provides library managers and those interested in developing academic search engines with data on the size and attributes of the academic invisible web.
  13. Schaer, P.; Mayr, P.; Sünkler, S.; Lewandowski, D.: How relevant is the long tail? : a relevance assessment study on million short (2016) 0.01 
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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. Lewandowski, D.: ¬Die Macht der Suchmaschinen und ihr Einfluss auf unsere Entscheidungen (2014) 0.01 
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    Date
    22. 9.2014 18:54:11
    Source
    Information - Wissenschaft und Praxis. 65(2014) H.4/5, S.231-238
  15. 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
  16. Lewandowski, D.: Web Information Retrieval : Technologien zur Informationssuche im Internet (2005) 0.01 
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    Abstract
    Verfahren des Information Retrieval haben in den letzten Jahren eine enorme Bedeutung erlangt. Während diese Verfahren jahrzehntelang nur Einsatz in spezialisierten Datenbanken fanden, haben sie durch das Aufkommen von Suchmaschinen im World Wide Web mittlerweile eine zentrale Bedeutung in der Informationsversorgung eingenommen. Verfahren des Web Information Retrieval entscheiden darüber, welche Informationen von Nutzern gefunden werden; man spricht auch von einer "Gatekeeper"-Funktion der Suchmaschinen. Diese sind zum bedeutendsten Rechercheinstrument sowohl im privaten, beruflichen als auch wissenschaftlichen Bereich avanciert. Google, die berühmteste der "Information-Retrieval-Firmen", ist fast täglich in den Schlagzeilen zu finden. Immer neue Innovationen (nicht nur dieses Anbieters) zeigen die Web-Suche als dynamisches Feld. Vor allem wird durch die zahlreichen Neuerungen der letzten Jahre, teilweise erst der letzten Monate, deutlich, dass die Suche im Web trotz ihrer mittlerweile fast zehnjährigen Geschichte erst am Anfang steht. Dass dem Web Information Retrieval eine hohe Bedeutung zugemessen wird, zeigt sich auch im wachsenden Interesse kommerzieller Unternehmen an diesem Thema. Ein Blick auf die Sponsorenliste der letztjährigen Konferenz der ACM Special Interest Group on Information Retrieval mag dies verdeutlichen: Neben den wichtigen Suchmaschinen-Anbietern Google, Microsoft, Yahoo und Ask Jeeves finden sich auch Großunternehmen wie IBM, Canon und Sharp. Auch in der gesellschaftlichen Diskussion sind die Suchmaschinen angekommen: Es findet gegenwärtig eine Diskussion um die "Google-Gesellschaft" statt, wobei gefragt wird, inwieweit ein einzelner Anbieter bzw. wenige Anbieter darüber entscheiden sollten, welche Informationen beim Nutzer angelangen. In dieser Hinsicht befassen sich inzwischen auch politische Parteien mit dem Thema. So publizierte etwa die Gründe Bundestagsfraktion ein Diskussionspapier unter dem Titel "Suchmaschinen: Tore zum Netz", in welchem unter anderem die Rolle der Suchmaschinen beim Zugang zu Informationen und Probleme des Datenschutzes bei der Suchmaschinennutzung angesprochen werden.
    Die vorliegende Arbeit setzt auf einer eher technischen Ebene an und bietet die Grundlagen für das Verständnis der Funktionsweise und der Defizite von Web-Suchmaschinen. Während zum klassischen Information Retrieval eine breite Auswahl an Literatur vorliegt, gibt es bisher kein Werk, welches eine umfassende Darstellung des Web Information Retrieval mit seinen Unterscheidungen und Besonderheiten gegenüber dem "klassischen" Information Retrieval bietet. Monographien zum Thema Suchmaschinen behandeln vor allem deren Suchfunktionen oder konzentrieren sich allein auf algorithmische Aspekte des Web Information Retrieval. Die Forschungslitertaur liegt zum überwältigenden Teil nur in englischer Sprache vor; die Forschung selbst findet zu einem großen Teil in den USA statt. Aus diesem Grund werden Spezifika anderer Sprachen als des Englischen sowie Besonderheiten auf nationaler oder gar kontinentaler Ebene vernachlässigt. Die Konsequenzen, die sich aus den Besonderheiten des Web Information Re¬trieval ergeben, wurden bisher nur unzureichend erkannt. Suchmaschinen orientieren sich noch stark am klassischen Information Retrieval, wenn auch teils eigene Rankingkriterien gefunden wurden, vor allem die Ergänzung der klassischen Faktoren durch eine Art der Qualitätsbewertung der indexierten Dokumente. Die Arbeit soll aufzeigen, welche Schritte nötig sind, um Web Information Retrieval vor allem auch in Hinblick auf die Charakteristika der Suchmaschinen-Nutzer effektiv zu gestalten. Die Verfahren des klassischen Information Retrieval versagen hier, da sie einerseits von einer gepflegten Dokumentenkollektion, andererseits von einem geschulten Nutzer ausgehen. Suchmaschinen haben mit Problemen des sog. Index-Spamming zu kämpfen: Hierbei werden (oft in kommerziellem Interesse) inhaltlich wertlose Dokumente erstellt, die in den Trefferlisten der Suchmaschinen auf den vorderen Rängen angezeigt werden sollen, um Nutzer auf eine bestimmte Webseite zu lenken. Zwar existieren Verfahren, die ein solches Spamming verhindern sollen, allerdings können auch diese das Problem lediglich eindämmen, nicht aber verhindern. Das Problem ließe sich wenigstens zum Teil durch die Nutzer lösen, wenn diese gezielte Suchanfragen stellen würden, die solche irrelevanten Treffer ausschließen würden. Allerdings zeigt die Nutzerforschung einheitlich, dass das Wissen der Nutzer über die von ihnen verwendeten Suchmaschinen ausgesprochen gering ist; dies gilt sowohl für ihre Kenntnisse der Funktionsweise der Suchmaschinen als auch die Kenntnis der Suchfunktionen.
    Die Arbeit konzentriert sich neben der Darstellung des Forschungsstands im Bereich des Web Information Retrieval auf einen nutzerzentrierten Ansatz des Aufbaus von Suchmaschinen, der sich aus dem Retrieval in klassischen Datenbanken herleitet. Als zentral für eine erfolgreiche Recherche wird dabei die Möglichkeit der gezielten Beschränkung der Recherche durch den Nutzer gesehen; die wichtigsten Faktoren sind hierbei die Einschränkung nach Aktualität, Qualität und die verbesserte Dokumentauswahl aufgrund einer erweiterten Dokumentrepräsentation. Alle drei Möglichkeiten sind in bisher verfügbaren Suchmaschinen nicht zufrieden stellend implementiert. Ein Problem bei der Bearbeitung des Themas ergab sich aus der Tatsache, dass die Forschung im Bereich Web Information Retrieval zu einem großen Teil bei den Anbietern selbst stattfindet, die darauf bedacht sind, ihre Erkenntnisse nicht zu veröffentlichen und damit der Konkurrenz zu überlassen. Viele Forschungsergebnisse können daher nur anhand der fertiggestellten Anwendungen rekonstruiert werden; hilfreich waren in manchen Fällen auch die von den Suchmaschinenbetreibern angemeldeten Patente, die für die vorliegende Arbeit ausgewertet wurden. Insgesamt zeigt sich, dass eine neue Form des Information Retrieval entstanden ist. Ziele des klassischen Information Retrieval wie die Vollständigkeit der Treffermenge verlieren ob der schieren Masse der zurückgegebenen Treffer an Bedeutung; dafür werden Faktoren der Qualitätsbewertung der Dokumente immer wichtiger. Das Web Information Retrieval setzt auf dem klassischen Information Retrieval auf und erweitert dieses wo nötig. Das Ziel bleibt aber weitgehend das gleiche: Dem Nutzer die für die Befriedigung seines Informationsbedürfnisses besten Ergebnisse zu liefern. Neben der Informationswissenschaft findet die Information-Retrieval-Forschung hauptsächlich in der Informatik statt. Der informationswissenschaftlichen Forschung kommt die Aufgabe zu, den stark technik-zentrierten Ansatz der Informatik um einen "Blick fürs Ganze" zu erweitern und insbesondere die Bedürfnisse der Nutzer in ihren Ansatz einzubinden. Aufgrund der enormen Bedeutung des Web Information Retrieval, welches in den klassischen informationswissenschaftlichen Bereich fällt, ergibt sich für die Informationswissenschaft auch die Chance, sich in diesem Thema gegenüber anderen Disziplinen zu profilieren. Zum Aufbau der Arbeit Die Arbeit lässt sich grob in zwei Hauptteile gliedern: Der erste Teil (Kap. 2-10) beschreibt den Bereich Web Information Retrieval mit allen seinen Besonderheiten in Abgrenzung zum klassischen Information Retrieval; der zweite Teil (Kap. 11-13) stellt anhand der Ergebnisse des ersten Teils einen nutzerzentrierten Ansatz der Rechercheverfeinerung in mehreren Schritten vor.
    Content
    Inhalt: 1 Einleitung 2 Forschungsumfeld 2.1 Suchmaschinen-Markt 2.2 Formen der Suche im WWW 2.3 Aufbau algorithmischer Suchmaschinen 2.4 Abfragesprachen 2.5 Arten von Suchanfragen 2.6 Nutzerstudien 2.7 Forschungsbereiche 3 Die Größe des Web und seine Abdeckung durch Suchmaschinen 3.1 Die Größe des indexierbaren Web 3.2 Die Struktur des Web 3.3 Crawling 3.4 Aktualität der Suchmaschinen 3.5 Das Invisible Web 4 Strukturinformationen 4.1 Strukturierungsgrad von Dokumenten 4.2 Strukturinformationen in den im Web gängigen Dokumenten 4.3 Trennung von Navigation, Layout und Inhalt 4.4 Repräsentation der Dokumente in den Datenbanken der Suchmaschinen 5 Klassische Verfahren des Information Retrieval und ihre Anwendung bei WWW-Suchmaschinen 5.1 Unterschiede zwischen klassischem Information Retrieval und Web Information Retrieval 5.2 Kontrolliertes Vokabular 5.3 Kriterien für die Aufnahme in den Datenbestand 5.4 Modelle des Information Retrieval 6 Ranking 6.1 Rankingfaktoren 6.2 Messbarkeit von Relevanz 6.3 Grundsätzliche Probleme des Relevance Ranking in Suchmaschinen
    Footnote
    Zugl. Diss. Univ. Düsseldorf, Inst. für Sprache und Information, Abt. Informationswissenschaft
    Rez. in: Information - Wissenschaft und Praxis. 56(2005) H.7, S.393-394 (J. Griesbaum): "... , das Buch wird seinem Titel und dem formulierten Anspruch sehr gut gerecht. Die 248 Seiten umfängliche Publikation leistet eine umfassende und, für den deutschsprachigen Raum, einzigartige State-of-the-Art-Analyse der Verfahren und auch der Defizite von Suchmaschinen im Internet. Dabei beschränkt sich Lewandowski nicht auf eine technikzentrierte Beschreibung aktueller Retrievalansätze, sondern akzentuiert ebenso deutlich auch die Problemfelder bei der Nutzung von Suchmaschinen. Dieser nutzerzentrierte Ansatz kommt vor allem im konzeptionellen Teil der Arbeit zum Tragen, der das Ziel verfolgt, Suchmaschinennutzern verbesserte Rechercheoptionen zu verschaffen. Angesichts der nur in geringem Maße vorhandenen Recherchekenntnisse der Nutzer liegt die Herausforderung vor allem darin, solche verbesserten Recherchemöglichkeiten derart auszugestalten, dass sie sich in realen Suchkontexten auch tatsächlich auswirken und nicht etwa wie die meist als "Erweitere Suche" bezeichneten Anfragemasken ein kaum beachtetes Dasein fristen. Der Verfasser konzipiert in diesem wichtigen Forschungsfeld neue Ansätze, um die Oualität des Information Retrievals zu verbessern. ... "
  17. Lewandowski, D.: ¬The retrieval effectiveness of search engines on navigational queries (2011) 0.01 
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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.
  18. Lewandowski, D.; Womser-Hacker, C.: Information seeking behaviour (2023) 0.01 
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    Abstract
    Die Vielzahl der Publikationen zeigt, dass Information Seeking Behaviour (ISB) bzw. Informationssuchverhalten in der informationswissenschaftlichen Forschung als relevantes Thema angesehen wird. ISB versteht sich als Unterkategorie von Information Behaviour (IB) bzw. Informationsverhalten, das jegliches menschliches Verhalten mit Bezug zu Wissen und Information umfasst, also z. B. auch Informationsvermeidung oder passives Informationsverhalten. ISB hingegen wurde anfänglich meist als bewusster Prozess verstanden, um sich aufgrund einer festgestellten Wissenslücke Information zu beschaffen. Information Seeking wird als eine alltägliche Aktivität angesehen, die meist dann auftritt, wenn eine informationell unterbestimmte Handlung durchgeführt werden soll
  19. Lewandowski, D.: Alles nur noch Google? : Entwicklungen im Bereich der WWW-Suchmaschinen (2002) 0.01 
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    Date
    29. 9.2002 18:49:22
  20. Lewandowski, D.: Query understanding (2011) 0.01 
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    Date
    18. 9.2018 18:22:18

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