Medical Surveillance, Frequent Sets, and Closure Operations

Alan P. Sprague and Stephen E. Brossette
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Alan P. Sprague: University of Alabama at Birmingham
Stephen E. Brossette: University of Alabama at Birmingham

Journal of Combinatorial Optimization, 2001, vol. 5, issue 1, No 6, 94 pages

Abstract: Abstract Surveillance of hospital-acquired infections, especially those caused by antibiotic resistant bacteria, is an important component of hospital infection control. A computer program for this purpose experienced a combinatorial computational explosion in time and space when processing data describing certain multi-drug resistant organisms. The blowup occurred while the program was generating frequent sets, a common phase in data mining algorithms. We present a modified algorithm for computing frequent sets that more efficiently handles the computational burden. The algorithm's proof of correctness involves the concepts of closure, independent sets, and circuits in a space more general than a matroid. Of central concern in the theory are inferences about a closure operation that can be obtained from limited information about the circuits.

Keywords: closure operation; data mining; frequent sets; medical surveillance (search for similar items in EconPapers)
Date: 2001
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DOI: 10.1023/A:1009889601723

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