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  • × theme_ss:"Retrievalstudien"
  1. Sünkler, S.: Prototypische Entwicklung einer Software für die Erfassung und Analyse explorativer Suchen in Verbindung mit Tests zur Retrievaleffektivität (2012) 0.00 
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    Imprint
    Hamburg : HAW, Department Information
  2. MacCain, K.W.; White, H.D.; Griffith, B.C.: Comparing retrieval performance in online data bases (1987) 0.00 
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    Source
    Information processing and management. 23(1987), S.539-553
  3. Lu, K.; Kipp, M.E.I.: Understanding the retrieval effectiveness of collaborative tags and author keywords in different retrieval environments : an experimental study on medical collections (2014) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 65(2014) no.3, S.483-500
  4. Ruthven, I.: Relevance behaviour in TREC (2014) 0.00 
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    Abstract
    Purpose - The purpose of this paper is to examine how various types of TREC data can be used to better understand relevance and serve as test-bed for exploring relevance. The author proposes that there are many interesting studies that can be performed on the TREC data collections that are not directly related to evaluating systems but to learning more about human judgements of information and relevance and that these studies can provide useful research questions for other types of investigation. Design/methodology/approach - Through several case studies the author shows how existing data from TREC can be used to learn more about the factors that may affect relevance judgements and interactive search decisions and answer new research questions for exploring relevance. Findings - The paper uncovers factors, such as familiarity, interest and strictness of relevance criteria, that affect the nature of relevance assessments within TREC, contrasting these against findings from user studies of relevance. Research limitations/implications - The research only considers certain uses of TREC data and assessment given by professional relevance assessors but motivates further exploration of the TREC data so that the research community can further exploit the effort involved in the construction of TREC test collections. Originality/value - The paper presents an original viewpoint on relevance investigations and TREC itself by motivating TREC as a source of inspiration on understanding relevance rather than purely as a source of evaluation material.
  5. 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
  6. 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.
  7. 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
  8. 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.
  9. Wartena, C.; Golub, K.: Evaluierung von Verschlagwortung im Kontext des Information Retrievals (2021) 0.00 
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  10. Lohmann, H.: KASCADE: Dokumentanreicherung und automatische Inhaltserschließung : Projektbericht und Ergebnisse des Retrievaltests (2000) 0.00 
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    RSWK
    Online-Katalog / Automatische Indexierung / Inhaltsverzeichnis / Scanning / Information Retrieval / Projekt
    Subject
    Online-Katalog / Automatische Indexierung / Inhaltsverzeichnis / Scanning / Information Retrieval / Projekt
  11. Dzeyk, W.: Effektiv und nutzerfreundlich : Einsatz von semantischen Technologien und Usability-Methoden zur Verbesserung der medizinischen Literatursuche (2010) 0.00 
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    Abstract
    In der vorliegenden Arbeit werden die Ergebnisse des MorphoSaurus-Projekts der Deutschen Zentralbibliothek für Medizin (ZB MED) vorgestellt. Ziel des Forschungsprojekts war die substanzielle Verbesserung des Information-Retrievals der medizinischen Suchmaschine MEDPILOT mithilfe computerlinguistischer Ansätze sowie die Optimierung der Gebrauchstauglichkeit (Usability) der Suchmaschinenoberfläche. Das Projekt wurde in Kooperation mit der Averbis GmbH aus Freiburg im Zeitraum von Juni 2007 bis Dezember 2008 an der ZB MED in Köln durchgeführt. Ermöglicht wurde die Realisierung des Projekts durch eine Förderung des Paktes für Forschung und Innovation. Während Averbis die MorphoSaurus-Technologie zur Verarbeitung problematischer Sprachaspekte von Suchanfragen einbrachte und wesentliche Datenbanken der ZB MED in ein Testsystem mit moderner Suchmaschinentechnologie implementierte, evaluierte ein Team der ZB MED das Potenzial dieser Technologie. Neben einem Vergleich der Leistungsfähigkeit zwischen der bisherigen MEDPILOT-Suche und der neuen Sucharchitektur wurde ein Benchmarking mit konkurrierenden Suchmaschinen wie PubMed, Scirus, Google und Google Scholar sowie GoPubMed durchgeführt. Für die Evaluation wurden verschiedene Testkollektionen erstellt, deren Items bzw. Suchphrasen aus einer Inhaltsanalyse realer Suchanfragen des MEDPILOT-Systems gewonnen wurden. Eine Überprüfung der Relevanz der Treffer der Testsuchmaschine als wesentliches Kriterium für die Qualität der Suche zeigte folgendes Ergebnis: Durch die Anwendung der MorphoSaurus-Technologie ist eine im hohen Maße unabhängige Verarbeitung fremdsprachlicher medizinischer Inhalte möglich geworden. Darüber hinaus zeigt die neue Technik insbesondere dort ihre Stärken, wo es um die gleichwertige Verarbeitung von Laien- und Expertensprache, die Analyse von Komposita, Synonymen und grammatikalischen Varianten geht. Zudem sind Module zur Erkennung von Rechtschreibfehlern und zur Auflösung von Akronymen und medizinischen Abkürzungen implementiert worden, die eine weitere Leistungssteigerung des Systems versprechen. Ein Vergleich auf der Basis von MEDLINE-Daten zeigte: Den Suchmaschinen MED-PILOT, PubMed, GoPubMed und Scirus war die Averbis-Testsuchumgebung klar überlegen. Die Trefferrelevanz war größer, es wurden insgesamt mehr Treffer gefunden und die Anzahl der Null-Treffer-Meldungen war im Vergleich zu den anderen Suchmaschinen am geringsten.

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