• DocumentCode
    3166442
  • Title

    Application of Data Mining for emotional intelligence based on cluster analysis

  • Author

    Jing, Feng ; Shiying, Kang

  • Author_Institution
    Chongqing Vocational Inst. of Electron. Eng., Chongqing, China
  • fYear
    2010
  • fDate
    29-30 Oct. 2010
  • Firstpage
    512
  • Lastpage
    515
  • Abstract
    Combining with the emotional intelligence theory, the Clustering Data Mining techniques was applied to individualized education research of Chongqing vocational Institute. through the emotional intelligence survey and its data collection, we dissected the characteristics of emotional intelligence data, analysed 804 samples of 5 Chongqing vocational Institute using K-means cluster analysis method. The 5 inner types of vocational students were dig out, including the balanced-type, strong adaptation-type, strong evaluation - type and weak regulation - type, strong adaptation-assessment-type, and weak awareness -strong evaluation-adaptation-type, etc. to provide the research basis for the development of more effective educational strategies.
  • Keywords
    artificial intelligence; data mining; emotion recognition; further education; statistical analysis; vocational training; K-means cluster analysis; data mining; emotional intelligence; higher vocational education; vocational students; Data mining; Educational institutions; Gravity; Psychology; Cluster analysis; Data mining; Emotional intelligence; Higher vocational education;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Education (ICAIE), 2010 International Conference on
  • Conference_Location
    Hangzhou
  • Print_ISBN
    978-1-4244-6935-2
  • Type

    conf

  • DOI
    10.1109/ICAIE.2010.5640962
  • Filename
    5640962