• DocumentCode
    518903
  • Title

    The reduction algorithm for dynamic information systems based on distinguishable relation

  • Author

    Chen, Xinying ; Xu, Kesheng

  • Author_Institution
    Sch. of Software Technol., Dalian Jiao Tong Univ., Dalian, China
  • Volume
    4
  • fYear
    2010
  • fDate
    27-29 March 2010
  • Firstpage
    60
  • Lastpage
    64
  • Abstract
    To capture a dynamic system with static reduction algorithm, the cost will enlarge a lot for the repeated work. Moreover, the algorithm can not catch partial changes in the system. To smooth this issue, a dynamic attribute reduction algorithm is introduced when the universe of the system keeps the same and the condition attribute set is added. The concept, Flagged Matrix, K-Flagged Matrix and Σ-Flagged Vector is defined and a reduction algorithm for dynamic information systems is given based on distinguishable relation. This algorithm will use the new added attributes and corresponding matrixes to correct and adjust the original attribute reduction. To do the reduction for the dynamic systems, as the theoretical illustration and empirical analysis turns out in this paper; the new added attributes are compared with the original attributes considering the distinguishable ability using corresponding matrixes. Then evaluate the added attributes are the core attributes or not, and determine whether the added attributes can replace the original attributes or not. After that, a new reduction is got. This algorithm can figure out the dynamic attribute reduction efficiently. For it will use matrix operation instead of logical operation, the cost of this algorithm is significantly decreased.
  • Keywords
    data mining; information systems; rough set theory; Σ-flagged vector; distinguishable relation; dynamic attribute reduction algorithm; dynamic information systems; dynamic systems; k-flagged matrix; static reduction algorithm; Costs; Delta modulation; Heuristic algorithms; Information systems; Knowledge representation; NP-hard problem; Set theory; Software algorithms; Uncertainty; data mining; distinguishable relation; dynamic reduction; rough set;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Control (ICACC), 2010 2nd International Conference on
  • Conference_Location
    Shenyang
  • Print_ISBN
    978-1-4244-5845-5
  • Type

    conf

  • DOI
    10.1109/ICACC.2010.5487231
  • Filename
    5487231