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Mielke, B.: Wider einige gängige Ansichten zur juristischen Informationserschließung (2002) 0.02

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Abstract: Ausgehend von einer Betrachtung in der Rechtsinformatik geläufiger Annahmen zur juristischen Informationserschließung beschreibt der Beitrag wesentliche Ergebnisse einer empirischen Studie der Retrievaleffektivität von Re-cherchen in juristischen Datenbanken. Dabei steht die Frage nach der Notwendigkeit einer intellektuellen Erschließung einerseits, der Effektivität der sogenannten Stichwortsuche andererseits im Mittelpunkt. Die Ergebnisse der Studie, bei der auch ein Vergleich zwischen einem Informationssystem auf der Basis eines Booleschen Retrievalmodells mit einem System auf der Basis statistischer Verfahren vorgenommen wurde, legen den Schluss nahe, dass in der rechtsinformatischen Fachliteratur analytisch begründete Annahmen wie die Gefahr zu großer Antwortmengen bei der Stichwortsuche empirisch nicht zu belegen sind. Auch zeigt sich keine Überlegenheit intellektueller Erschließungsverfahren (Beschlagwortung) gegenüber der automatischen Indexierung, im Gegenteil führt der Einsatz eines statistischen Verfahrens bei identischer Dokumentkollektion zu einer höheren Wiedergewinnungsrate (recall).
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

Günther, M.: Vermitteln Suchmaschinen vollständige Bilder aktueller Themen? : Untersuchung der Gewichtung inhaltlicher Aspekte von Suchmaschinenergebnissen in Deutschland und den USA (2016) 0.02

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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.

Griesbaum, J.; Rittberger, M.; Bekavac, B.: Deutsche Suchmaschinen im Vergleich : AltaVista.de, Fireball.de, Google.de und Lycos.de (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

Schirrmeister, N.-P.; Keil, S.: Aufbau einer Infrastruktur für Information Retrieval-Evaluationen (2012) 0.01

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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.

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.

Content

Die Studie wurde auf der diesjährigen CLEF-Konferenz mit dem Best Poster Award ausgezeichnet.

Footnote

To appear in Experimental IR Meets Multilinguality, Multimodality, and Interaction. 7th International Conference of the CLEF Association, CLEF 2016, \'Evora, Portugal, September 5-8, 2016.
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.

Hider, P.: ¬The search value added by professional indexing to a bibliographic database (2017) 0.00

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Content: Beitrag bei: NASKO 2017: Visualizing Knowledge Organization: Bringing Focus to Abstract Realities. The sixth North American Symposium on Knowledge Organization (NASKO 2017), June 15-16, 2017, in Champaign, IL, USA.

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