Search (26 results, page 1 of 2)

  • × theme_ss:"Data Mining"
  1. Schwartz, D.: Graphische Datenanalyse für digitale Bibliotheken : Leistungs- und Funktionsumfang moderner Analyse- und Visualisierungsinstrumente (2006) 0.08 
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    Abstract
    Das World Wide Web stellt umfangreiche Datenmengen zur Verfügung. Für den Benutzer wird es zunehmend schwieriger, diese Datenmengen zu sichten, zu bewerten und die relevanten Daten herauszufiltern. Einen Lösungsansatz für diese Problemstellung bieten Visualisierungsinstrumente, mit deren Hilfe Rechercheergebnisse nicht mehr ausschließlich über textbasierte Dokumentenlisten, sondern über Symbole, Icons oder graphische Elemente dargestellt werden. Durch geeignete Visualisierungstechniken können Informationsstrukturen in großen Datenmengen aufgezeigt werden. Informationsvisualisierung ist damit ein Instrument, um Rechercheergebnisse in einer digitalen Bibliothek zu strukturieren und relevante Daten für den Benutzer leichter auffindbar zu machen.
    Theme
    Visualisierung
  2. Keim, D.A.: Data Mining mit bloßem Auge (2002) 0.02 
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    Abstract
    Visualisierungen, die möglichst instruktive grafische Darstellung von Daten, ist wesentlicher Bestandteil des Data Mining
  3. Information visualization in data mining and knowledge discovery (2002) 0.01 
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    Date
    23. 3.2008 19:10:22
    RSWK
    Visualisierung / Computergraphik / Data Mining
    Visualisierung (BVB)
    Data Mining / Visualisierung / Aufsatzsammlung (BVB)
    Wissensextraktion / Visualisierung / Aufsatzsammlung (BVB)
    Subject
    Visualisierung / Computergraphik / Data Mining
    Visualisierung (BVB)
    Data Mining / Visualisierung / Aufsatzsammlung (BVB)
    Wissensextraktion / Visualisierung / Aufsatzsammlung (BVB)
    Theme
    Visualisierung
  4. Datentracking in der Wissenschaft : Aggregation und Verwendung bzw. Verkauf von Nutzungsdaten durch Wissenschaftsverlage. Ein Informationspapier des Ausschusses für Wissenschaftliche Bibliotheken und Informationssysteme der Deutschen Forschungsgemeinschaft (2021) 0.01 
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    Abstract
    Das Informationspapier beschreibt die digitale Nachverfolgung von wissenschaftlichen Aktivitäten. Wissenschaftlerinnen und Wissenschaftler nutzen täglich eine Vielzahl von digitalen Informationsressourcen wie zum Beispiel Literatur- und Volltextdatenbanken. Häufig fallen dabei Nutzungsspuren an, die Aufschluss geben über gesuchte und genutzte Inhalte, Verweildauern und andere Arten der wissenschaftlichen Aktivität. Diese Nutzungsspuren können von den Anbietenden der Informationsressourcen festgehalten, aggregiert und weiterverwendet oder verkauft werden. Das Informationspapier legt die Transformation von Wissenschaftsverlagen hin zu Data Analytics Businesses dar, verweist auf die Konsequenzen daraus für die Wissenschaft und deren Einrichtungen und benennt die zum Einsatz kommenden Typen der Datengewinnung. Damit dient es vor allem der Darstellung gegenwärtiger Praktiken und soll zu Diskussionen über deren Konsequenzen für die Wissenschaft anregen. Es richtet sich an alle Wissenschaftlerinnen und Wissenschaftler sowie alle Akteure in der Wissenschaftslandschaft.
  5. Wattenberg, M.; Viégas, F.; Johnson, I.: How to use t-SNE effectively (2016) 0.01 
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    Theme
    Visualisierung
  6. Maaten, L. van den: Learning a parametric embedding by preserving local structure (2009) 0.01 
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    Theme
    Visualisierung
  7. Maaten, L. van den: Accelerating t-SNE using Tree-Based Algorithms (2014) 0.01 
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    Theme
    Visualisierung
  8. Leydesdorff, L.; Persson, O.: Mapping the geography of science : distribution patterns and networks of relations among cities and institutes (2010) 0.01 
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    Theme
    Visualisierung
  9. Kraker, P.; Kittel, C,; Enkhbayar, A.: Open Knowledge Maps : creating a visual interface to the world's scientific knowledge based on natural language processing (2016) 0.01 
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    Theme
    Visualisierung
  10. Maaten, L. van den; Hinton, G.: Visualizing non-metric similarities in multiple maps (2012) 0.01 
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    Theme
    Visualisierung
  11. Maaten, L. van den; Hinton, G.: Visualizing data using t-SNE (2008) 0.00 
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    Theme
    Visualisierung
  12. Chowdhury, G.G.: Template mining for information extraction from digital documents (1999) 0.00 
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    Date
    2. 4.2000 18:01:22
  13. KDD : techniques and applications (1998) 0.00 
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    Footnote
    A special issue of selected papers from the Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'97), held Singapore, 22-23 Feb 1997
  14. Matson, L.D.; Bonski, D.J.: Do digital libraries need librarians? (1997) 0.00 
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    Date
    22.11.1998 18:57:22
  15. Lusti, M.: Data Warehousing and Data Mining : Eine Einführung in entscheidungsunterstützende Systeme (1999) 0.00 
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    Date
    17. 7.2002 19:22:06
  16. Amir, A.; Feldman, R.; Kashi, R.: ¬A new and versatile method for association generation (1997) 0.00 
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    Source
    Information systems. 22(1997) nos.5/6, S.333-347
  17. Hofstede, A.H.M. ter; Proper, H.A.; Van der Weide, T.P.: Exploiting fact verbalisation in conceptual information modelling (1997) 0.00 
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    Source
    Information systems. 22(1997) nos.5/6, S.349-385
  18. Lackes, R.; Tillmanns, C.: Data Mining für die Unternehmenspraxis : Entscheidungshilfen und Fallstudien mit führenden Softwarelösungen (2006) 0.00 
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    Date
    22. 3.2008 14:46:06
  19. Hallonsten, O.; Holmberg, D.: Analyzing structural stratification in the Swedish higher education system : data contextualization with policy-history analysis (2013) 0.00 
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    Date
    22. 3.2013 19:43:01
  20. Vaughan, L.; Chen, Y.: Data mining from web search queries : a comparison of Google trends and Baidu index (2015) 0.00 
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    Source
    Journal of the Association for Information Science and Technology. 66(2015) no.1, S.13-22

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  • e 16
  • d 10

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