• DocumentCode
    3335340
  • Title

    An improved Apriori algorithm for association rules of mining

  • Author

    Wei Yong-qing ; Yang Ren-hua ; Liu Pei-yu

  • Author_Institution
    Shandong Police Coll., Ji´nan, China
  • Volume
    1
  • fYear
    2009
  • fDate
    14-16 Aug. 2009
  • Firstpage
    942
  • Lastpage
    946
  • Abstract
    Apriori -the classical association rules mining algorithm is a way to find out certain potential, regular knowledge from the massive ones. But there are two more serious defects in the data mining process. The first needs many times to scan the business database and the second will inevitably produce a large number of irrelevant candidate sets which seriously occupy the system resources. An improved method is introduced on the basic of the defects above. The improved algorithm only scans the database once, at the same time the discrete data and statistics related are completed, and the final one is to prune the candidate item sets according to the minimum supporting degree and the character of the frequent item sets. After analysis, the improved algorithm reduces the system resources occupied and improves the efficiency and quality.
  • Keywords
    data mining; database management systems; association mining rule; business database; data mining process; frequent item set character; improved apriori algorithm; Algorithm design and analysis; Association rules; Data mining; Databases; Educational institutions; Frequency; Information science; Itemsets; Knowledge engineering; Statistics;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    IT in Medicine & Education, 2009. ITIME '09. IEEE International Symposium on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-1-4244-3928-7
  • Electronic_ISBN
    978-1-4244-3930-0
  • Type

    conf

  • DOI
    10.1109/ITIME.2009.5236211
  • Filename
    5236211