Search (10 results, page 1 of 1)

  • × theme_ss:"Retrievalstudien"
  • × type_ss:"el"
  1. Griesbaum, J.; Rittberger, M.; Bekavac, B.: Deutsche Suchmaschinen im Vergleich : AltaVista.de, Fireball.de, Google.de und Lycos.de (2002) 0.02 
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    Source
    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. Günther, M.: Vermitteln Suchmaschinen vollständige Bilder aktueller Themen? : Untersuchung der Gewichtung inhaltlicher Aspekte von Suchmaschinenergebnissen in Deutschland und den USA (2016) 0.01 
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    Abstract
    Zielsetzung - Vor dem Hintergrund von Suchmaschinenverzerrungen sollte herausgefunden werden, ob sich die von Google und Bing vermittelten Bilder aktueller internationaler Themen in Deutschland und den USA hinsichtlich (1) Vollständigkeit, (2) Abdeckung und (3) Gewichtung der jeweiligen inhaltlichen Aspekte unterscheiden. Forschungsmethoden - Für die empirische Untersuchung wurde eine Methode aus Ansätzen der empirischen Sozialwissenschaften (Inhaltsanalyse) und der Informationswissenschaft (Retrievaltests) entwickelt und angewandt. Ergebnisse - Es zeigte sich, dass Google und Bing in Deutschland und den USA (1) keine vollständigen Bilder aktueller internationaler Themen vermitteln, dass sie (2) auf den ersten Trefferpositionen nicht die drei wichtigsten inhaltlichen Aspekte abdecken, und dass es (3) bei der Gewichtung der inhaltlichen Aspekte keine signifikanten Unterschiede gibt. Allerdings erfahren diese Ergebnisse Einschränkungen durch die Methodik und die Auswertung der empirischen Untersuchung. Schlussfolgerungen - Es scheinen tatsächlich inhaltliche Suchmaschinenverzerrungen vorzuliegen - diese könnten Auswirkungen auf die Meinungsbildung der Suchmaschinennutzer haben. Trotz großem Aufwand bei manueller, und qualitativ schlechteren Ergebnissen bei automatischer Untersuchung sollte dieses Thema weiter erforscht werden.
    Content
    Vgl.: https://yis.univie.ac.at/index.php/yis/article/view/1355. Diesem Beitrag liegt folgende Abschlussarbeit zugrunde: Günther, Markus: Welches Weltbild vermitteln Suchmaschinen? Untersuchung der Gewichtung inhaltlicher Aspekte von Google- und Bing-Ergebnissen in Deutschland und den USA zu aktuellen internationalen Themen . Masterarbeit (M.A.), Hochschule für Angewandte Wissenschaften Hamburg, 2015. Volltext: http://edoc.sub.uni-hamburg.de/haw/volltexte/2016/332.
    Source
    Young information scientists. 1(2016), S.13-29
  3. Sünkler, S.: Prototypische Entwicklung einer Software für die Erfassung und Analyse explorativer Suchen in Verbindung mit Tests zur Retrievaleffektivität (2012) 0.01 
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    Abstract
    Gegenstand dieser Arbeit ist die Entwicklung eines funktionalen Prototyps einer Webanwendung für die Verknüpfung der Evaluierung von explorativen Suchen in Verbindung mit der Durchführung klassisches Retrievaltests. Als Grundlage für die Programmierung des Prototyps werden benutzerorientierte und systemorientierte Evalulierungsmethoden für Suchmaschinen analysiert und in einem theoretischen Modell zur Untersuchung von Informationssysteme und Suchmaschinen kombiniert. Bei der Gestaltung des Modells und des Prototyps wird gezeigt, wie sich aufgezeichnete Aktionsdaten praktisch für die Suchmaschinenevaluierung verwenden lassen, um auf der einen Seite eine Datengrundlage für Retrievaltests zu gewinnen und andererseits, um für die Auswertung von Relevanzbewertungen auch das implizierte Feedback durch Handlungen der Anwender zu berücksichtigen. Retrievaltests sind das gängige und erprobte Mittel zur Messung der Retrievaleffektiviät von Informationssystemen und Suchmaschinen, verzichten aber auf eine Berücksichtigung des tatsächlichen Nutzerverhaltens. Eine Methode für die Erfassung der Interaktionen von Suchmaschinennutzern sind protokollbasierte Tests, mit denen sich Logdateien über Benutzer einer Anwendung generieren lassen. Die im Rahmen der Arbeit umgesetzte Software bietet einen Ansatz, Retrievaltests auf Basis protokollierter Nutzerdaten in Verbindung mit kontrollierten Suchaufgaben, durchzuführen. Das Ergebnis dieser Arbeit ist ein fertiger funktionaler Prototyp, der in seinem Umfang bereits innerhalb von Suchmaschinenstudien nutzbar ist.
    Content
    Masterarbeit im Studiengang Informationswissenschaft und -management.
    Imprint
    Hamburg : HAW, Department Information
  4. Mielke, B.: Wider einige gängige Ansichten zur juristischen Informationserschließung (2002) 0.01 
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    Source
    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
  5. Schirrmeister, N.-P.; Keil, S.: Aufbau einer Infrastruktur für Information Retrieval-Evaluationen (2012) 0.00 
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    Abstract
    Das Projekt "Aufbau einer Infrastruktur für Information Retrieval-Evaluationen" (AIIRE) bietet eine Softwareinfrastruktur zur Unterstützung von Information Retrieval-Evaluationen (IR-Evaluationen). Die Infrastruktur basiert auf einem Tool-Kit, das bei GESIS im Rahmen des DFG-Projekts IRM entwickelt wurde. Ziel ist es, ein System zu bieten, das zur Forschung und Lehre am Fachbereich Media für IR-Evaluationen genutzt werden kann. This paper describes some aspects of a project called "Aufbau einer Infrastruktur für Information Retrieval-Evaluationen" (AIIRE). Its goal is to build a software-infrastructure which supports the evaluation of information retrieval algorithms.
  6. Hofmann, M.: TREC Konferenzbericht (7.10.93) (1995) 0.00 
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    Abstract
    Ziel der US-amerikanischen TREC (Texte REtrieval Conference) Initiative ist es, zum einen Standard-Kollektionen von Teten zu erstellen, auf deren Basis verschiedene Retrieval-Ansätze verglichen werden können. Zum anderen sollen Kollektionen einer Grösse aufgebaut werden, die realistischen Anwendungen nahe kommen. Damit soll das alte Vorurteil der Untauglichkeit neuerer IR-Methoden (bzgl. Effizienz und Effektivität) für größere Darenbasen widerlegt werden.
  7. Borlund, P.: ¬The IIR evaluation model : a framework for evaluation of interactive information retrieval systems (2003) 0.00 
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    Source
    Information Research. 8(2003), no.3
  8. Robertson, S.E.; Sparck Jones, K.: Simple, proven approaches to text retrieval (1997) 0.00 
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    Abstract
    This technical note describes straightforward techniques for document indexing and retrieval that have been solidly established through extensive testing and are easy to apply. They are useful for many different types of text material, are viable for very large files, and have the advantage that they do not require special skills or training for searching, but are easy for end users. The document and text retrieval methods described here have a sound theoretical basis, are well established by extensive testing, and the ideas involved are now implemented in some commercial retrieval systems. Testing in the last few years has, in particular, shown that the methods presented here work very well with full texts, not only title and abstracts, and with large files of texts containing three quarters of a million documents. These tests, the TREC Tests (see Harman 1993 - 1997; IP&M 1995), have been rigorous comparative evaluations involving many different approaches to information retrieval. These techniques depend an the use of simple terms for indexing both request and document texts; an term weighting exploiting statistical information about term occurrences; an scoring for request-document matching, using these weights, to obtain a ranked search output; and an relevance feedback to modify request weights or term sets in iterative searching. The normal implementation is via an inverted file organisation using a term list with linked document identifiers, plus counting data, and pointers to the actual texts. The user's request can be a word list, phrases, sentences or extended text.
  9. 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.
  10. Toepfer, M.; Seifert, C.: Content-based quality estimation for automatic subject indexing of short texts under precision and recall constraints 0.00 
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    Abstract
    Semantic annotations have to satisfy quality constraints to be useful for digital libraries, which is particularly challenging on large and diverse datasets. Confidence scores of multi-label classification methods typically refer only to the relevance of particular subjects, disregarding indicators of insufficient content representation at the document-level. Therefore, we propose a novel approach that detects documents rather than concepts where quality criteria are met. Our approach uses a deep, multi-layered regression architecture, which comprises a variety of content-based indicators. We evaluated multiple configurations using text collections from law and economics, where the available content is restricted to very short texts. Notably, we demonstrate that the proposed quality estimation technique can determine subsets of the previously unseen data where considerable gains in document-level recall can be achieved, while upholding precision at the same time. Hence, the approach effectively performs a filtering that ensures high data quality standards in operative information retrieval systems.

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