Search (64 results, page 1 of 4)

  • × theme_ss:"Visualisierung"
  1. Reiterer, H.; Jetter, H.-C.: Informationsvisualisierung (2013) 0.04
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    Source
    Grundlagen der praktischen Information und Dokumentation. Handbuch zur Einführung in die Informationswissenschaft und -praxis. 6., völlig neu gefaßte Ausgabe. Hrsg. von R. Kuhlen, W. Semar u. D. Strauch. Begründet von Klaus Laisiepen, Ernst Lutterbeck, Karl-Heinrich Meyer-Uhlenried
  2. Chen, C.: CiteSpace II : detecting and visualizing emerging trends and transient patterns in scientific literature (2006) 0.02
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    Abstract
    This article describes the latest development of a generic approach to detecting and visualizing emerging trends and transient patterns in scientific literature. The work makes substantial theoretical and methodological contributions to progressive knowledge domain visualization. A specialty is conceptualized and visualized as a time-variant duality between two fundamental concepts in information science: research fronts and intellectual bases. A research front is defined as an emergent and transient grouping of concepts and underlying research issues. The intellectual base of a research front is its citation and co-citation footprint in scientific literature - an evolving network of scientific publications cited by research-front concepts. Kleinberg's (2002) burst-detection algorithm is adapted to identify emergent research-front concepts. Freeman's (1979) betweenness centrality metric is used to highlight potential pivotal points of paradigm shift over time. Two complementary visualization views are designed and implemented: cluster views and time-zone views. The contributions of the approach are that (a) the nature of an intellectual base is algorithmically and temporally identified by emergent research-front terms, (b) the value of a co-citation cluster is explicitly interpreted in terms of research-front concepts, and (c) visually prominent and algorithmically detected pivotal points substantially reduce the complexity of a visualized network. The modeling and visualization process is implemented in CiteSpace II, a Java application, and applied to the analysis of two research fields: mass extinction (1981-2004) and terrorism (1990-2003). Prominent trends and pivotal points in visualized networks were verified in collaboration with domain experts, who are the authors of pivotal-point articles. Practical implications of the work are discussed. A number of challenges and opportunities for future studies are identified.
    Date
    22. 7.2006 16:11:05
  3. Wu, K.-C.; Hsieh, T.-Y.: Affective choosing of clustering and categorization representations in e-book interfaces (2016) 0.02
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    Date
    20. 1.2015 18:30:22
  4. Wu, I.-C.; Vakkari, P.: Effects of subject-oriented visualization tools on search by novices and intermediates (2018) 0.02
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    Date
    9.12.2018 16:22:25
  5. Eito Brun, R.: Retrieval effectiveness in software repositories : from faceted classifications to software visualization techniques (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
  6. Keil-Slawik, R.: Konzepte digitaler Medien : semantische Karten, räumliche Strukturierung von Wissen (2005) 0.01
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  7. Kocijan, K.: Visualizing natural language resources (2015) 0.01
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    Source
    Re:inventing information science in the networked society: Proceedings of the 14th International Symposium on Information Science, Zadar/Croatia, 19th-21st May 2015. Eds.: F. Pehar, C. Schloegl u. C. Wolff
  8. Reiterer, H.: Visuelle Recherchesysteme zur Unterstützung der Wissensverarbeitung (2004) 0.01
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    Source
    Wissen in Aktion: Der Primat der Pragmatik als Motto der Konstanzer Informationswissenschaft. Festschrift für Rainer Kuhlen. Hrsg. R. Hammwöhner, u.a
  9. Leissler, M.; Hemmje, M: Portierung und Erweiterung der Relevanzkugelmetapher des LyberWorld-Werkzeuges um interaktive Informationsvisualisierungsmechanismen (1997) 0.01
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    Type
    r
  10. Samoylenko, I.; Chao, T.-C.; Liu, W.-C.; Chen, C.-M.: Visualizing the scientific world and its evolution (2006) 0.01
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  11. Haller, S.H.M.: Mappingverfahren zur Wissensorganisation (2002) 0.01
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    Date
    30. 5.2010 16:22:35
  12. Platis, N. et al.: Visualization of uncertainty in tag clouds (2016) 0.01
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    Date
    1. 2.2016 18:25:22
  13. Sidhom, S.; Hassoun, M.: Morpho-syntactic parsing to text mining environment : NP recognition model to knowledge visualization and information (2003) 0.01
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    Source
    Tendencias de investigación en organización del conocimient: IV Cologuio International de Ciencas de la Documentación , VI Congreso del Capitulo Espanol de ISKO = Trends in knowledge organization research. Eds.: J.A. Frias u. C. Travieso
  14. Börner, K.: Atlas of knowledge : anyone can map (2015) 0.01
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    Date
    22. 1.2017 16:54:03
    22. 1.2017 17:10:56
  15. Miller, C.: Virtual reality and online databases : will "look and feel" literally mean "look" and "feel"? (1992) 0.01
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  16. Collins, C.: WordNet explorer : applying visualization principles to lexical semantics (2006) 0.01
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  17. Tscherteu, G.; Langreiter, C.: Explorative Netzwerkanalyse im Living Web (2009) 0.01
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  18. Eckert, K: ¬The ICE-map visualization (2011) 0.01
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    Type
    r
  19. Denton, W.: On dentographs, a new method of visualizing library collections (2012) 0.01
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    Abstract
    A dentograph is a visualization of a library's collection built on the idea that a classification scheme is a mathematical function mapping one set of things (books or the universe of knowledge) onto another (a set of numbers and letters). Dentographs can visualize aspects of just one collection or can be used to compare two or more collections. This article describes how to build them, with examples and code using Ruby and R, and discusses some problems and future directions.
  20. Trunk, D.: Semantische Netze in Informationssystemen : Verbesserung der Suche durch Interaktion und Visualisierung (2005) 0.01
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    Date
    30. 1.2007 18:22:41

Years

Languages

  • e 46
  • d 17
  • a 1
  • More… Less…

Types

  • a 48
  • el 12
  • m 8
  • r 3
  • s 2
  • x 2
  • b 1
  • More… Less…