DocumentCode :
476308
Title :
College teachers subhealth decision analyzing by using improved association rules
Author :
Qin, Feng-zhen
Author_Institution :
Dept. of Phys. Educ, Central China Normal Univ., Wuhan
Volume :
6
fYear :
2008
fDate :
12-15 July 2008
Firstpage :
3540
Lastpage :
3544
Abstract :
With the high development of science and technology, the progresses of society, the increasing pressure of modern work, the trend of peoplepsilas health states is dropping gradually. The number of people in subhealthy state is enlarging day by day. Many researchers have done a lot of researches on the constitution health data of college teachers by traditional math analyzing method. Some superficial information is obtained easily though traditional query operation from constitution data, but deep level information that hides in the constitution data is difficult to be discovered. Based on it, an improved association algorithm is proposed and applied in constitution health data analyzing. The results manifest that the algorithm is effective in constitution health data analyzing.
Keywords :
data mining; college teachers; constitution data; data mining; improved association rules; subhealth decision; Algorithm design and analysis; Association rules; Constitution; Data analysis; Data mining; Databases; Educational institutions; Educational technology; Machine learning; Statistics; Aprior; Constitution data; Data Mining; Subhealthy;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location :
Kunming
Print_ISBN :
978-1-4244-2095-7
Electronic_ISBN :
978-1-4244-2096-4
Type :
conf
DOI :
10.1109/ICMLC.2008.4621017
Filename :
4621017
Link To Document :
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