• 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