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  • × theme_ss:"Social tagging"
  1. Sack, H.; Waitelonis, J.: Zeitbezogene kollaborative Annotation zur Verbesserung der inhaltsbasierten Videosuche (2008) 0.03 
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    Abstract
    Social-Tagging-Systeme ermöglichen die Annotation beliebiger Ressourcen mit nutzerbasierten Metadaten. Ressourcen wurden in diesem Zusammenhang stets als Ganzes betrachtet, ohne dass eine differenzierte Annotation einzelner Ressourcen-Fragmente möglich war. Dies fällt insbesondere bei zeitabhängigen Multimediadaten, wie z. B. Videodaten ins Gewicht, da der Nutzer oft nur an einzelnen Szenen einer umfangreichen Videodatei interessiert ist. Dieser Beitrag stellt eine einfache Möglichkeit der zeitbezogenen, kollaborativen Annotation von Multimediadaten vor und veranschaulicht deren Umsetzung am Beispiel der Videosuchmaschine yovisto.
    Source
    Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a
  2. Hotho, A.; Jäschke, R.; Benz, D.; Grahl, M.; Krause, B.; Schmitz, C.; Stumme, G.: Social Bookmarking am Beispiel BibSonomy (2009) 0.03 
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    Source
    Social Semantic Web: Web 2.0, was nun? Hrsg.: A. Blumauer u. T. Pellegrini
  3. Held, C.; Cress, U.: Social Tagging aus kognitionspsychologischer Sicht (2008) 0.03 
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    Source
    Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a
  4. Golbeck, J.; Koepfler, J.; Emmerling, B.: ¬An experimental study of social tagging behavior and image content (2011) 0.03 
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  5. Lin, N.; Li, D.; Ding, Y.; He, B.; Qin, Z.; Tang, J.; Li, J.; Dong, T.: ¬The dynamic features of Delicious, Flickr, and YouTube (2012) 0.03 
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    Abstract
    This article investigates the dynamic features of social tagging vocabularies in Delicious, Flickr, and YouTube from 2003 to 2008. Three algorithms are designed to study the macro- and micro-tag growth as well as the dynamics of taggers' activities, respectively. Moreover, we propose a Tagger Tag Resource Latent Dirichlet Allocation (TTR-LDA) model to explore the evolution of topics emerging from those social vocabularies. Our results show that (a) at the macro level, tag growth in all the three tagging systems obeys power law distribution with exponents lower than 1; at the micro level, the tag growth of popular resources in all three tagging systems follows a similar power law distribution; (b) the exponents of tag growth vary in different evolving stages of resources; (c) the growth of number of taggers associated with different popular resources presents a feature of convergence over time; (d) the active level of taggers has a positive correlation with the macro-tag growth of different tagging systems; and (e) some topics evolve into several subtopics over time while others experience relatively stable stages in which their contents do not change much, and certain groups of taggers continue their interests in them.
  6. Voß, J.: Vom Social Tagging zum Semantic Tagging (2008) 0.03 
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    Source
    Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a
  7. Blank, M.; Bopp, T.; Hampel, T.; Schulte, J.: Social Tagging = Soziale Suche? (2008) 0.03 
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    Source
    Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a
  8. Tschetschonig, K.; Ladengruber, R.; Hampel, T.; Schulte, J.: Kollaborative Tagging-Systeme im Electronic Commerce (2008) 0.03 
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    Source
    Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a
  9. Müller-Prove, M.: Modell und Anwendungsperspektive des Social Tagging (2008) 0.03 
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    Pages
    S.15-22
    Source
    Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a
  10. Web-2.0-Dienste als Ergänzung zu algorithmischen Suchmaschinen (2008) 0.02 
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    Abstract
    Mit sozialen Suchdiensten - wie z. B. Yahoo Clever, Lycos iQ oder Mister Wong - ist eine Ergänzung und teilweise sogar eine Konkurrenz zu den bisherigen Ansätzen in der Web-Suche entstanden. Während Google und Co. automatisch generierte Trefferlisten bieten, binden soziale Suchdienste die Anwender zu Generierung der Suchergebnisse in den Suchprozess ein. Vor diesem Hintergrund wird in diesem Buch der Frage nachgegangen, inwieweit soziale Suchdienste mit traditionellen Suchmaschinen konkurrieren oder diese qualitativ ergänzen können. Der vorliegende Band beleuchtet die hier aufgeworfene Fragestellung aus verschiedenen Perspektiven, um auf die Bedeutung von sozialen Suchdiensten zu schließen.
    Editor
    Lewandowski, D. u. C. Maaß
  11. Matthews, B.; Jones, C.; Puzon, B.; Moon, J.; Tudhope, D.; Golub, K.; Nielsen, M.L.: ¬An evaluation of enhancing social tagging with a knowledge organization system (2010) 0.02 
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  12. Harrer, A.; Lohmann, S.: Potenziale von Tagging als partizipative Methode für Lehrportale und E-Learning-Kurse (2008) 0.02 
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    Date
    21. 6.2009 12:22:44
    Source
    Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a
  13. Niemann, C.: Intelligenz im Chaos : erste Schritte zur Analyse des Kreativen Potenzials eines Tagging-Systems (2010) 0.02 
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    Abstract
    Die Auszeichnung digitaler Medien durch Tagging ist zur festen Größe für das Wissensmanagement im Internet avanciert. Im Kontext des zunehmenden information overload' stehen wissenschaftliche Bibliotheken vor der Aufgabe, die große Flut digital publizierter Artikel und Werke möglichst inhaltlich erschlossen verfügbar zu machen. Die Frage ist, ob durch den Einsatz von Tagging-Systemen die kollaborative Intelligenz der NutzerInnen für die Sacherschließung eingesetzt werden kann, während diese von einer intuitiven und individuellen Wissensorganisation profitieren. Die große Freiheit bei der Vergabe von Deskriptoren durch die NutzerInnen eines Tagging-Systems ist nämlich ein ambivalentes Phänomen: Kundennähe und kreatives Potenzial stehen der großen Menge völlig unkontrollierter Meta-Informationen gegenüber, deren inhaltliche Qualität und Aussagekraft noch unklar ist. Bisherige Forschungsbemühungen konzentrieren sich hauptsächlich auf die automatische Hierarchisierung bzw. Relationierung der Tag-Daten (etwa mittels Ähnlichkeitsalgorithmen) oder auf die Analyse des (Miss-)Erfolgs, den die NutzerInnen bei einer Suchanfrage subjektiv erfahren. Aus der Sicht stark strukturierter Wissensorganisation, wie sie Experten z. B. durch die Anwendung von Klassifikationen realisieren, handelt es sich bei den zunächst unvermittelt nebeneinander stehenden Tags allerdings kurz gesagt um Chaos. Dass in diesem Chaos aber auch Struktur und wertvolles Wissen als Gemeinschaftsprodukt erzeugt werden kann, ist eine der zentralen Thesen dieses Artikels.
    Source
    ¬The Ne(x)t generation: das Angebot der Bibliotheken; 30. Österreichischer Bibliothekartag, Graz, 15.-18.9.2009. Hrsg.: Ute Bergner u. Erhard Göbel
  14. Li, D.; Ding, Y.; Sugimoto, C.; He, B.; Tang, J.; Yan, E.; Lin, N.; Qin, Z.; Dong, T.: Modeling topic and community structure in social tagging : the TTR-LDA-Community model (2011) 0.02 
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  15. Estrada, L.M.; Hildebrand, M.; Boer, V. de; Ossenbruggen, J. van: Time-based tags for fiction movies : comparing experts to novices using a video labeling game (2017) 0.02 
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    Abstract
    The cultural heritage sector has embraced social tagging as a way to increase both access to online content and to engage users with their digital collections. In this article, we build on two current lines of research. (a) We use Waisda?, an existing labeling game, to add time-based annotations to content. (b) In this context, we investigate the role of experts in human-based computation (nichesourcing). We report on a small-scale experiment in which we applied Waisda? to content from film archives. We study the differences in the type of time-based tags between experts and novices for film clips in a crowdsourcing setting. The findings show high similarity in the number and type of tags (mostly factual). In the less frequent tags, however, experts used more domain-specific terms. We conclude that competitive games are not suited to elicit real expert-level descriptions. We also confirm that providing guidelines, based on conceptual frameworks that are more suited to moving images in a time-based fashion, could result in increasing the quality of the tags, thus allowing for creating more tag-based innovative services for online audiovisual heritage.
  16. Kruk, S.R.; Kruk, E.; Stankiewicz, K.: Evaluation of semantic and social technologies for digital libraries (2009) 0.02 
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    Date
    1. 8.2010 12:35:22
    Source
    Semantic digital libraries. Eds.: S.R. Kruk, B. McDaniel
  17. Rolla, P.J.: User tags versus Subject headings : can user-supplied data improve subject access to library collections? (2009) 0.02 
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    Date
    10. 9.2000 17:38:22
    Type
    b
  18. Strader, C.R.: Author-assigned keywords versus Library of Congress Subject Headings : implications for the cataloging of electronic theses and dissertations (2009) 0.02 
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    Date
    10. 9.2000 17:38:22
    Type
    b
  19. Simon, J.: Interdisciplinary knowledge creation : using wikis in science (2006) 0.02 
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    Source
    Knowledge organization for a global learning society: Proceedings of the 9th International ISKO Conference, 4-7 July 2006, Vienna, Austria. Hrsg.: G. Budin, C. Swertz u. K. Mitgutsch
  20. Lüth, J.: Inhaltserschließung von Internetquellen durch Nutzerinnen und Nutzer : Ergebnisse eines Tests mit Internetquellen der Virtuellen Fachbibliothek EconBiz (2009) 0.02 
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    Abstract
    EconBiz, die Virtuelle Fachbibliothek Wirtschaftswissenschaften, wird gemeinsam von der Deutschen Zentralbibliothek für Wirtschaftswissenschaften (ZBW) und der Universitäts- und Stadtbibliothek Köln angeboten. Ein zentraler Bestandteil von EconBiz ist der Fachinformationsführer für Internetquellen, der derzeit über 16.000 Datensätze umfasst. Der Fachinformationsführer dient der Recherche nach Internetquellen und frei verfügbaren Volltexten. Die Erschließung dieser Quellen erfolgt arbeitsteilig durch bibliothekarisches und wissenschaftliches Personal im LinkShare System, einem System für die kooperative Erschließung und Verwaltung digitaler Netzobjekte. Nutzerinnen und Nutzer von EconBiz haben die Möglichkeit, Quellen für die Aufnahme in den Fachinformationsführer vorzuschlagen. Eine Beteiligung an der inhaltlichen Erschließung der Quellen erfolgt nicht. In Social-Bookmarking-Portalen wie "deLicio.us", "Furl" oder "Mister Wong" haben Nutzerinnen und Nutzer die Möglichkeit, eigene Listen mit Lesezeichen, englisch "Bookmarks", zu verwalten. Dazu bieten die verschiedenen Anbieter dieser Dienste allerhand nützliche Funktionen, u. a. mit folgenden Merkmalen: - Vergabe von Kategorien oder Schlagworten, so genannten "Tags", - Anlegen privater oder öffentlicher Bookmarks, - Abspeichern einer Version der Quelle. Derzeit üben diese Dienste eine sehr hohe Anziehungskraft auf Nutzerinnen und Nutzer aus, zum einen für die Verwaltung der eigenen Lesezeichen, zum anderen als Instrument für die Recherche nach relevanten Quellen. Mehr über das Potential und die Einsatzmöglichkeiten von Social-Bookmarking-Diensten möchte die ZBW im Rahmen eines Projekts "Inhaltserschließung durch Nutzerinnen und Nutzer" erfahren. Dafür wurde über einen begrenzten Zeitraum eine Teilmenge der im EconBiz-Fachinformationsführer enthaltenen Internetquellen in Social-Bookmarking-Webseiten angeboten. Ziel ist es, Erkenntnisse darüber zu gewinnen, in welchem Umfang diese von den Nutzerinnen und Nutzern der Socaial-Bookmarking-Dienste nachgenutzt und um eigene Schlagworte ergänzt werden.

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