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Measuring the quality of network visualization
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Source International Conference on Digital Libraries archive
Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries table of contents
Denver, CO, USA
DEMONSTRATION SESSION: Demonstrations table of contents
Pages: 405 - 405  
Year of Publication: 2005
ISBN:1-58113-876-8
Author
Chaomei Chen  Drexel University, Philadelphia, PA
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 4,   Downloads (12 Months): 32,   Citation Count: 0
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ABSTRACT

A quantitative method is developed for measuring the quality of network visualizations in terms of log-likelihood metrics resulted from Expectation Maximization (EM) clustering intrinsic and extrinsic attributes of network nodes.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Chen, C. Information Visualization: Beyond the Horizon. London: Springer Verlag.
 
2
Chen, C. Searching for intellectual turning points: Progressive Knowledge Domain Visualization. Proc. Natl. Acad. Sci. USA, 101 (2004), 5303--5310.
 
3
Chen, C. CiteSpace. http://cluster.cis.drexel.edu/~cchen

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.2 User Interfaces (D.2.2, H.1.2, I.3.6)
          Subjects: Graphical user interfaces (GUI)


General Terms:
Algorithms, Measurement, Verification


Keywords:
EM clustering, network visualization, quality metrics of quality

Collaborative Colleagues:
Chaomei Chen: colleagues

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