Search (47 results, page 2 of 3)

  • × theme_ss:"Social tagging"
  1. Derntl, M.; Hampel, T.; Motschnig, R.; Pitner, T.: Social Tagging und Inclusive Universal Access (2008) 0.01 
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    Source
    Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a
  2. Kuchler, T.; Pawlowski, J.M.; Zimmermann, V.: Social Tagging and Open Content : a concept for the future of e-learning and knowledge management? (2008) 0.01 
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    Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a
  3. Schillerwein, S.: ¬Der 'Business Case' für die Nutzung von Social Tagging in Intranets und internen Informationssystemen (2008) 0.01 
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    Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a
  4. Braun, S.; Schmidt, A.; Walter, A.; Zacharias, V.: Von Tags zu semantischen Beziehungen : kollaborative Ontologiereifung (2008) 0.01 
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    Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a
  5. Güntner, G.; Sint, R.; Westenthaler, R.: ¬Ein Ansatz zur Unterstützung traditioneller Klassifikation durch Social Tagging (2008) 0.01 
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    Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a
  6. Pammer, V.; Ley, T.; Lindstaedt, S.: tagr: Unterstützung in kollaborativen Tagging-Umgebungen durch semantische und assoziative Netzwerke (2008) 0.01 
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    Good tags - bad tags: Social Tagging in der Wissensorganisation. Hrsg.: B. Gaiser, u.a
  7. Heuwing, B.: Erfahrungen an der Universitätsbibliothek Hildesheim : Social Tagging in Bibliotheken (2010) 0.01 
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  8. Web-2.0-Dienste als Ergänzung zu algorithmischen Suchmaschinen (2008) 0.01 
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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.
  9. Golbeck, J.; Koepfler, J.; Emmerling, B.: ¬An experimental study of social tagging behavior and image content (2011) 0.01 
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  10. Niemann, C.: Tag-Science : Ein Analysemodell zur Nutzbarkeit von Tagging-Daten (2011) 0.01 
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    Source
    ¬Die Kraft der digitalen Unordnung: 32. Arbeits- und Fortbildungstagung der ASpB e. V., Sektion 5 im Deutschen Bibliotheksverband, 22.-25. September 2009 in der Universität Karlsruhe. Hrsg: Jadwiga Warmbrunn u.a
  11. Hammond, T.; Hannay, T.; Lund, B.; Flack, M.: Social bookmarking tools (II) : a case study - Connotea (2005) 0.01 
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  12. Stvilia, B.; Jörgensen, C.: Member activities and quality of tags in a collection of historical photographs in Flickr (2010) 0.01 
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  13. Niemann, C.: Intelligenz im Chaos : erste Schritte zur Analyse des Kreativen Potenzials eines Tagging-Systems (2010) 0.01 
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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.
  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) 0.01 
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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) 0.01 
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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. Danowski, P.: Authority files and Web 2.0 : Wikipedia and the PND. An Example (2007) 0.01 
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    Content
    Vortrag anlässlich des Workshops: "Extending the multilingual capacity of The European Library in the EDL project Stockholm, Swedish National Library, 22-23 November 2007".
  17. Chen, M.; Liu, X.; Qin, J.: Semantic relation extraction from socially-generated tags : a methodology for metadata generation (2008) 0.01 
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    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  18. Kim, H.L.; Scerri, S.; Breslin, J.G.; Decker, S.; Kim, H.G.: ¬The state of the art in tag ontologies : a semantic model for tagging and folksonomies (2008) 0.01 
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    Metadata for semantic and social applications : proceedings of the International Conference on Dublin Core and Metadata Applications, Berlin, 22 - 26 September 2008, DC 2008: Berlin, Germany / ed. by Jane Greenberg and Wolfgang Klas
  19. Yi, K.: Harnessing collective intelligence in social tagging using Delicious (2012) 0.01 
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    Date
    25.12.2012 15:22:37
  20. Choi, Y.; Syn, S.Y.: Characteristics of tagging behavior in digitized humanities online collections (2016) 0.01 
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    Date
    21. 4.2016 11:23:22

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