Dynamic maintenance of decision rules with rough set under characteristic relation

Tianrui Li, Da Ruan, Jing Song

    Research outputpeer-review

    Abstract

    Rough sets for knowledge update have been successfully applied in data mining. Methods for incremental updating decision rules based on the indiscernibility, tolerance relation and similarity relations in rough set theory have been previously studied in literature. The characteristic relation-based rough sets approach provides more informative results than the approach employing the indiscernibility, tolerance relations and similarity relations based approach. In this paper, we extend rough sets based on characteristic relations for incrementally updating decision rules. An extensive experimental evaluation validates the efficiency of the proposed approach which may be used to handle a dynamic maintenance of decision rules in data mining.

    Original languageEnglish
    Title of host publication2007 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2007
    Publisher IEEE Computer Society and the Association for Computing Machinery
    Pages3713-3716
    Number of pages4
    ISBN (Print)1424413125, 1424413125, 9781424413126, 9781424413126
    DOIs
    StatePublished - 2007
    Event2007 - WiCOM: International Conference on Wireless Communications, Networking and Mobile Computing - Shanghai
    Duration: 21 Sep 200725 Sep 2007
    https://ieeexplore.ieee.org/xpl/conhome/4339774/proceeding

    Publication series

    Name2007 International Conference on Wireless Communications, Networking and Mobile Computing, WiCOM 2007

    Conference

    Conference2007 - WiCOM
    Country/TerritoryChina
    CityShanghai
    Period2007-09-212007-09-25
    Internet address

    ASJC Scopus subject areas

    • Computer Science Applications
    • Electrical and Electronic Engineering
    • Communication

    Cite this