TY - JOUR
T1 - Research on Algorithm in Association Rule in an Early Warning System of College Students
AU - Zhou, Li Juan
AU - Li, Shuang
AU - Zhang, Zhang
JF - Key Engineering Materials
VL - 460-461
SP - 445
EP - 450
SN - 1662-9795
PY - 2011
PB - Trans Tech Publications
DO - 10.4028/www.scientific.net/KEM.460-461.445
UR - http://www.scientific.net/KEM.460-461.445
KW - Apriori Algorithm
KW - Association Rule
KW - Early Warning System
AB - 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.
ER -