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QAPgrid: A Two Level QAP-Based Approach for Large-Scale Data Analysis and Visualization

Overview of attention for article published in PLOS ONE, January 2011
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Title
QAPgrid: A Two Level QAP-Based Approach for Large-Scale Data Analysis and Visualization
Published in
PLOS ONE, January 2011
DOI 10.1371/journal.pone.0014468
Pubmed ID
Authors

Mario Inostroza-Ponta, Regina Berretta, Pablo Moscato

Abstract

The visualization of large volumes of data is a computationally challenging task that often promises rewarding new insights. There is great potential in the application of new algorithms and models from combinatorial optimisation. Datasets often contain "hidden regularities" and a combined identification and visualization method should reveal these structures and present them in a way that helps analysis. While several methodologies exist, including those that use non-linear optimization algorithms, severe limitations exist even when working with only a few hundred objects.

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Mendeley readers

The data shown below were compiled from readership statistics for 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 4%
Portugal 1 4%
Australia 1 4%
Unknown 23 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 31%
Researcher 7 27%
Student > Master 5 19%
Other 2 8%
Student > Doctoral Student 1 4%
Other 2 8%
Unknown 1 4%
Readers by discipline Count As %
Computer Science 9 35%
Agricultural and Biological Sciences 6 23%
Social Sciences 3 12%
Engineering 3 12%
Mathematics 2 8%
Other 3 12%