• DocumentCode
    130974
  • Title

    Application of improved association rule algorithm in the courses management

  • Author

    Hua Wang ; Ping Liu ; Hongyang Li

  • Author_Institution
    Inf. Eng. Inst., Capital Normal Univ., Beijing, China
  • fYear
    2014
  • fDate
    27-29 June 2014
  • Firstpage
    804
  • Lastpage
    807
  • Abstract
    Apriori is a classical association rule algorithm, On the basis of analyzing the Apriori algorithm and some improved algorithms, Using Matlab tool implements an efficient algorithm, the improved algorithm largely reduces the size of candidate sets and improves the mining efficiency. Finally, the improved algorithm is applied in the university curriculum management, which uses students´ academic records as data source to mining the hidden curriculum related rules. And other relevant metrics such as lift, all confidence and cosine are introduced to verify the correlation of association rules. These will be significance to provide the significance information for teaching management.
  • Keywords
    data mining; educational administrative data processing; educational institutions; teaching; Matlab tool; apriori algorithm; association rule algorithm; courses management; data source; mining efficiency; students academic records; teaching management; university curriculum management; Apriori algorithm; algorithm efficiency; association rules; course correlation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
  • Conference_Location
    Beijing
  • ISSN
    2327-0586
  • Print_ISBN
    978-1-4799-3278-8
  • Type

    conf

  • DOI
    10.1109/ICSESS.2014.6933688
  • Filename
    6933688