• DocumentCode
    2982561
  • Title

    Research of Data Mining Technology in Electronic Commerce

  • Author

    Pan, QingChao

  • Author_Institution
    Coll. of Phys. Sci. & Technol., Shenyang Normal Univ., Shenyang, China
  • fYear
    2011
  • fDate
    12-14 Aug. 2011
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The characteristics of e-commerce are described. The function and technology of data mining are analyzed. The processes of data mining in electronic commerce are discussed. A new improved algorithm is proposed through analyzing the advantages and disadvantages of Fp-growth association rules mining. It is proved that the improved algorithm has higher efficiency and lesser memory cost than Fp-growth algorithm by the experimental results.
  • Keywords
    data mining; electronic commerce; Fp-growth association rules mining; data mining technology; electronic commerce; less memory cost; Algorithm design and analysis; Association rules; Business; Classification algorithms; Databases; Electronic commerce;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management and Service Science (MASS), 2011 International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-6579-8
  • Type

    conf

  • DOI
    10.1109/ICMSS.2011.5999185
  • Filename
    5999185
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2982561