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Classified Information: The Data Clustering Problem
September/October 2003 (vol. 5 no. 5)
pp. 54-60
Nargess Memarsadeghi, University of Maryland
Dianne P. O'Leary, University of Maryland
Yalin E. Sagduyu, University of Maryland

Many projects in engineering and science require data classification based on different heuristics. Designers, for example, classify automobile engine performance as acceptable or unacceptable based on a combination of efficiency, emissions, noise levels, and other criteria. Researchers routinely classify documents as "relevant to the current project" or "irrelevant." Genome decoding divides chromosomes into genes, regulatory regions, signals, and so on. Pathologists identify cells as cancerous or benign.

Citation:
Nargess Memarsadeghi, Dianne P. O'Leary, Yalin E. Sagduyu, "Classified Information: The Data Clustering Problem," Computing in Science and Engineering, vol. 5, no. 5, pp. 54-60, Sept.-Oct. 2003, doi:10.1109/MCISE.2003.1225861
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