Research on Algorithm in Association Rule in an Early Warning System of College Students

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The student early warning is a type of the problem that involves intelligence factor and non-intelligence factor and indetermination factor, the challenge lies in ascertaining early-warning factor. In this paper, basing on analyzing association rule and the principle of Apriori algorithm, a new Apriori algorithm has been designed for solving complexity of predictors in an early warning system of college students. At first, make sure the count K of item gathering the largest frequent itemset. Then directly make the largest frequent itemset LK by the items, whose count of item is larger than K or equal to K. We can acquire the k-1、k-2 frequent itemset with the same method. We carry on an experiment on the new algorithm. As a result, the efficiency of the new Algorithm is raised obviously. And along with data quantity aggrandizement, the time consumed changes inconspicuously. That is to say the algorithm keeps very high efficiency.

Info:

Periodical:

Key Engineering Materials (Volumes 460-461)

Edited by:

Yanwen Wu

Pages:

445-450

DOI:

10.4028/www.scientific.net/KEM.460-461.445

Citation:

L. J. Zhou et al., "Research on Algorithm in Association Rule in an Early Warning System of College Students", Key Engineering Materials, Vols. 460-461, pp. 445-450, 2011

Online since:

January 2011

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Price:

$35.00

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