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Algebraic visual analysis: the Catalano phone call data set case study
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International Conference on Knowledge Discovery and Data Mining archive
Proceedings of the ACM SIGKDD Workshop on Visual Analytics and Knowledge Discovery: Integrating Automated Analysis with Interactive Exploration table of contents
Paris, France
Pages 74-82  
Year of Publication: 2009
ISBN:978-1-60558-670-0
Authors
Anna A. Shaverdian  University of Michigan
Hao Zhou  University of Michigan
George Michailidis  University of Michigan
H. V. Jagadish  University of Michigan
Sponsors
: PASCAL2 - Pattern Analysis, Statistical Modelling and Computational Learning
: Helsinki Institute for Information Technology HIIT
: VisMaster, a European FP7 Coordination Action Project focused on Visual Analytics
: Danube University Krems, Departement of Information and Knowledge Engineering (DUK)
: National Visualization and Analytics Center (NVAC)
Publisher
ACM  New York, NY, USA
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ABSTRACT

While many clever techniques have been proposed for visual analysis, most of these are "one of" and it is not easy to see how to combine multiple techniques. We propose an algebraic model capable of representing a large class of visual analysis operations on graph data. We demonstrate the value of this model by showing how it can simulate the analyses performed by several groups on the Catalano family cell phone call record data set as part of the VAST 2008 challenge.


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:
Anna A. Shaverdian: colleagues
Hao Zhou: colleagues
George Michailidis: colleagues
H. V. Jagadish: colleagues