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Interactive visual clustering
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Source International Conference on Intelligent User Interfaces archive
Proceedings of the 12th international conference on Intelligent user interfaces table of contents
Honolulu, Hawaii, USA
SESSION: Short papers table of contents
Pages: 361 - 364  
Year of Publication: 2007
ISBN:1-59593-481-2
Authors
Marie desJardins  University of Maryland Baltimore County, Baltimore, MD
James MacGlashan  University of Maryland Baltimore County, Baltimore, MD
Julia Ferraioli  Bryn Mawr College, Bryn Mawr, PA
Sponsors
ACM: Association for Computing Machinery
SIGART: ACM Special Interest Group on Artificial Intelligence
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
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ABSTRACT

Interactive Visual Clustering (IVC) is a novel method that allows a user to explore relational data sets interactively, in order to produce a clustering that satisfies their objectives. IVC combines spring-embedded graph layout with user interaction and constrained clustering. Experimental results on several synthetic and real-world data sets show that IVC yields better clustering performance than alternative methods.


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.

 
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Collaborative Colleagues:
Marie desJardins: colleagues
James MacGlashan: colleagues
Julia Ferraioli: colleagues