• DocumentCode
    2293189
  • Title

    Investigation and application of extension data mining based on rough set

  • Author

    Tang, Zhi-Hang ; Yang, Bao-An

  • Author_Institution
    Sch. of Comput. & Commun., Hunan Inst. of Eng., Xiangtan, China
  • fYear
    2009
  • fDate
    14-16 Sept. 2009
  • Firstpage
    112
  • Lastpage
    118
  • Abstract
    In the database of information system, usually there are some attributes which are unimportant to the decision attribute, and some records that disturb the decision making. In this paper, reducing the condition attributes based on the matter-element theory and rough set method, calculating the importance to the decision attribute for each condition attribute after reduction, and data mining the relevant rules based on the reduced attributes, extension relevant function is used to depict quality of data gather in data mining. Finally, how to tap new customers and how to recommend an appropriate brand to new customers, Research result indicates that extension data mining can provide effective decide support for the decision-making of enterprise.
  • Keywords
    data mining; decision making; rough set theory; condition attribute reduction; customer service; database; decision attribute; decision making; extension data mining; extension relevant function; information system; matter-element theory; rough set method; Conference management; Data analysis; Data engineering; Data mining; Databases; Decision making; Engineering management; Information systems; Machine learning; Rough sets; attributes reduction; extension data mining; matter-element; rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Management Science and Engineering, 2009. ICMSE 2009. International Conference on
  • Conference_Location
    Moscow
  • Print_ISBN
    978-1-4244-3970-6
  • Electronic_ISBN
    978-1-4244-3971-3
  • Type

    conf

  • DOI
    10.1109/ICMSE.2009.5318868
  • Filename
    5318868