• DocumentCode
    568130
  • Title

    The application of data mining technology based on teaching information

  • Author

    Wang, Jian ; Lu, Zhubin ; Wu, Weihua ; Li, Yuzhou

  • Author_Institution
    Coll. of Appl. Technol., Southwest Univ., Chongqing, China
  • fYear
    2012
  • fDate
    14-17 July 2012
  • Firstpage
    652
  • Lastpage
    657
  • Abstract
    Data mining deepens the data analysis, also is able to mine the interesting mode hiding in mass data automatically. As a new data analysis technology, data mining makes full use of the modern software technology and computer scientific knowledge, has the extremely important research significance, provides for researchers of various fields with a new intelligence means to realize and use data. In data mining, association rule learning is a popular and well researched method for discovering interesting relations between variables in large databases. This paper makes a series of data analysis and research on the application of data mining technology in the students´ scores. This paper use Apriori algorithm of association rules to analyze the intrinsic link among various courses, dig out the precedence relationship and association of students´ learning courses, reveal the teaching regularities and problems from large amount of data, as well as to provide a strong basis for reasonable course-setting.
  • Keywords
    data analysis; data mining; educational technology; teaching; Apriori algorithm; association rule learning; computer scientific knowledge; data analysis; data mining technology; modern software technology; teaching information; Algorithm design and analysis; Association rules; Education; Itemsets; Association Rule; Data Mining; Frequent Itemsets;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Science & Education (ICCSE), 2012 7th International Conference on
  • Conference_Location
    Melbourne, VIC
  • Print_ISBN
    978-1-4673-0241-8
  • Type

    conf

  • DOI
    10.1109/ICCSE.2012.6295159
  • Filename
    6295159