Search (70 results, page 1 of 4)

  • × theme_ss:"Visualisierung"
  1. Platis, N. et al.: Visualization of uncertainty in tag clouds (2016) 0.04
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    Date
    1. 2.2016 18:25:22
    Source
    Semantic keyword-based search on structured data sources: First COST Action IC1302 International KEYSTONE Conference, IKC 2015, Coimbra, Portugal, September 8-9, 2015. Revised Selected Papers. Eds.: J. Cardoso et al
  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. Oh, K.E.; Halpern, D.; Tremaine, M.; Chiang, J.; Silver, D.; Bemis, K.: Blocked: when the information is hidden by the visualization (2016) 0.02
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    Abstract
    This study investigated how people comprehend three-dimensional (3D) visualizations and what properties of such visualizations affect comprehension. Participants were asked to draw the face of a 3D visualization after it was cut in half. We videotaped the participants as they drew, erased, verbalized their thoughts, gestured, and moved about a two-dimensional paper presentation of the 3D visualization. The videorecords were analyzed using a grounded theory approach to generate hypotheses related to comprehension difficulties and visualization properties. Our analysis of the results uncovered three properties that made problem solving more difficult for participants. These were: (a) cuts that were at an angle in relation to at least one plane of reference, (b) nonplanar properties of the features contained in the 3D visualizations including curved layers and v-shaped layers, and (c) mixed combinations of layers. In contrast, (a) cutting planes that were perpendicular or parallel to the 3D visualization diagram's planes of reference, (b) internal features that were flat/planar, and (c) homogeneous layers were easier to comprehend. This research has direct implications for the generation and use of 3D information visualizations in that it suggests design features to include and avoid.
  4. Brockelmann, M.; Wolff, C.: 3D-Visualisierungen : Potenziale in Forschung und Lehre im Kontext von Informationswissenschaft und Medieninformatik (2013) 0.02
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    Content
    Vgl.: http://www.degruyter.com/view/j/iwp.2013.64.issue-4/wp-2013-0031/wp-2013-0031.xml?format=INT.
  5. 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
  6. 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
  7. Leide, J.E.; Large, A.; Beheshti, J.; Brooks, M.; Cole, C.: Visualization schemes for domain novices exploring a topic space : the navigation classification scheme (2003) 0.02
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  8. Information visualization : human-centered issues and perspectives (2008) 0.02
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    Content
    Inhalt: Part I. General Reflections The Value of Information Visualization / Jean-Daniel Fekete, Jarke J van Wijk, John T. Stasko, Chris North Evaluating Information Visualizations / Sheelagh Carpendale Theoretical Foundations of Information Visualization / Helen C. Purchase, Natalia Andrienko, T.J. Jankun-Kelly, Matthew Ward Teaching Information Visualization / Andreas Kerren, John T. Stasko, Jason Dykes Part II. Specific Aspects Creation and Collaboration: Engaging New Audiences for Information Visualization / Jeffrey Heer, Frank van Ham, Sheelagh Carpendale, Chris Weaver, Petra Isenberg Process and Pitfalls in Writing Information Visualization Research Papers / Tamara Munzner Visual Analytics: Definition, Process, and Challenges / Daniel Keim, Gennady Andrienko, Jean-Daniel Fekete, Carsten Görg, Jörn Kohlhammer, Guy Melancon
  9. 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
  10. Saß, J.: Bestandsvisualisierung in Bibliotheken (2015) 0.01
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  11. Zhang, J.: TOFIR: A tool of facilitating information retrieval : introduce a visual retrieval model (2001) 0.01
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  12. 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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  13. Haller, S.H.M.: Mappingverfahren zur Wissensorganisation (2002) 0.01
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    Date
    30. 5.2010 16:22:35
  14. 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
  15. Reiterer, H.; Jetter, H.-C.: Informationsvisualisierung (2013) 0.01
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  16. 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
  17. Miller, C.: Virtual reality and online databases : will "look and feel" literally mean "look" and "feel"? (1992) 0.01
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  18. Collins, C.: WordNet explorer : applying visualization principles to lexical semantics (2006) 0.01
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    Date
    30. 1.2007 18:22:41

Years

Languages

  • e 56
  • d 13
  • a 1
  • More… Less…

Types

  • a 59
  • el 10
  • m 7
  • s 2
  • x 2
  • b 1
  • More… Less…