• DocumentCode
    365
  • Title

    A Rough-Set-Based Incremental Approach for Updating Approximations under Dynamic Maintenance Environments

  • Author

    Chen, Hongmei ; Li, Tianrui ; Ruan, Da ; Lin, Jianhui ; Hu, Chengxiang

  • Author_Institution
    Sch. of Inf. Sci. & Technol., Southwest Jiaotong Univ., Chengdu, China
  • Volume
    25
  • Issue
    2
  • fYear
    2013
  • fDate
    Feb. 2013
  • Firstpage
    274
  • Lastpage
    284
  • Abstract
    Approximations of a concept by a variable precision rough-set model (VPRS) usually vary under a dynamic information system environment. It is thus effective to carry out incremental updating approximations by utilizing previous data structures. This paper focuses on a new incremental method for updating approximations of VPRS while objects in the information system dynamically alter. It discusses properties of information granulation and approximations under the dynamic environment while objects in the universe evolve over time. The variation of an attribute´s domain is also considered to perform incremental updating for approximations under VPRS. Finally, an extensive experimental evaluation validates the efficiency of the proposed method for dynamic maintenance of VPRS approximations.
  • Keywords
    approximation theory; data structures; granular computing; information systems; maintenance engineering; precision engineering; rough set theory; TRS model; VPRS approximations; attribute domain; data structures; dynamic information system environment; dynamic maintenance environments; extensive experimental evaluation; information approximations; information granulation; rough-set-based incremental approach; variable precision rough-set model; Approximation algorithms; Approximation methods; Computational modeling; Electronic mail; Information systems; Knowledge discovery; Precision engineering; Rough sets; Variable precision rough-set model; granular computing; incremental updating; information systems; knowledge discovery;
  • fLanguage
    English
  • Journal_Title
    Knowledge and Data Engineering, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1041-4347
  • Type

    jour

  • DOI
    10.1109/TKDE.2011.220
  • Filename
    6051434