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  • × year_i:[2000 TO 2010}
  • × author_ss:"Chen, C."
  1. Chen, C.: Top Ten Problems in Visual Interfaces to Digital Libraries (2002) 0.07
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    Date
    22. 2.2003 17:25:39
    22. 2.2003 18:13:11
    Source
    Visual Interfaces to Digital Libraries. Eds.: Börner, K. u. C. Chen
  2. Börner, K.; Chen, C.: Visual Interfaces to Digital Libraries : Motivation, Utilization, and Socio-technical Challenges (2002) 0.07
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    Date
    22. 2.2003 17:25:39
    22. 2.2003 18:20:07
    Source
    Visual Interfaces to Digital Libraries. Eds.: Börner, K. u. C. Chen
  3. 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
  4. Chen, C.: Visualizing scientific paradigms : an introduction (2003) 0.01
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  5. Chen, C.; Kuljis, J.: ¬The rising landscape : a visual exploration of superstring revolutions in physics (2003) 0.01
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  6. Chen, C.; Paul, R.J.; O'Keefe, B.: Fitting the Jigsaw of citation : information visualization in domain analysis (2001) 0.01
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  7. Chen, C.; Cribbin, T.; Macredie, R.; Morar, S.: Visualizing and tracking the growth of competing paradigms : two case studies (2002) 0.01
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  8. Chen, C.; Ibekwe-SanJuan, F.; Pinho, R.; Zhang, J.: ¬The impact of the sloan digital sky survey on astronomical research : the role of culture, identity, and international collaboration (2008) 0.01
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  9. Chen, C.; Czerwinski, M.; Macredie, R.: Individual differences in virtual environments : introduction and overview (2000) 0.00
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  10. Chen, C.: Individual differences in a spatial-semantic virtual environment (2000) 0.00
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  11. Chen, C.: Mapping scientific frontiers : the quest for knowledge visualization (2003) 0.00
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  12. Börner, K.; Chen, C.; Boyack, K.W.: Visualizing knowledge domains (2002) 0.00
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