• DocumentCode
    3096397
  • Title

    A Modified Characteristic Relation for Incomplete Data

  • Author

    Xuri, Yin

  • Author_Institution
    Simulation Lab. of Mil. Traffic, Inst. of Automobile Manage. of PLA, Bengbu
  • fYear
    2008
  • fDate
    21-22 Dec. 2008
  • Firstpage
    132
  • Lastpage
    135
  • Abstract
    In the classical rough set theory, the use of the indiscernibility relation which is used in the complete information systems may be too rigid in some real situations. In order to process incomplete data, the indiscernibility relation needs to be extended. In this paper, after discussing the basic concepts and current research on the characteristic relation under incomplete data, a modified characteristic relation that is dependent on the number of missing values with respect to the number of the whole defined attributes for each object is introduced; the lower and upper approximation defined on this relation are proposed as well. Furthermore, we present some properties of this modified characteristic relation. The experiments show that this relation works effectively in incomplete information and generates object classification reasonably. This electronic document is a "live" template. The various components of your paper [title, text, heads, etc.] are already defined on the style sheet, as illustrated by the portions given in this document.
  • Keywords
    data handling; rough set theory; complete information systems; incomplete data; incomplete information; modified characteristic relation; object classification; rough set theory; Automobiles; Character generation; Information systems; Knowledge management; Laboratories; Management information systems; Programmable logic arrays; Rough sets; Set theory; Traffic control; characteristic relation; incomplete data; missing value; rough set theory;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Acquisition and Modeling Workshop, 2008. KAM Workshop 2008. IEEE International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-3530-2
  • Electronic_ISBN
    978-1-4244-3531-9
  • Type

    conf

  • DOI
    10.1109/KAMW.2008.4810442
  • Filename
    4810442