• DocumentCode
    2124509
  • Title

    Research on Knowledge Acquisition Approach in Decision-Making System Based on Rough Sets Theory and Its Application

  • Author

    Ling, Wang ; Pei, Hu

  • Author_Institution
    Coll. of Econ. & Manage., Southwest Jiaotong Univ., Chengdu
  • fYear
    2008
  • fDate
    21-22 Dec. 2008
  • Firstpage
    147
  • Lastpage
    151
  • Abstract
    A kind of knowledge acquisition approach in decision-making system based on rough sets theory is proposed. In this paper the basic concepts and characters of rough sets is firstly overviewed. Then with decision attribute importance applied in decision-making system,the degree of dependency supplied by decision-making attribute for the condition attribute is described and the degree of attribute importance was obtained to calculate attribute core. Secondly, let relative reduction of attribute as heuristic information, a new attribute reduction algorithm of decision table is proposed. Thirdly, according to the reduced decision table, the attribute value reduction algorithm based on core value is designed and then with these algorithm steps, corresponding decision rules are extracted from original decision data sets. Finally, through analyzing an example, the practical results show that the approach is effective in solving knowledge acquisition.
  • Keywords
    decision making; knowledge acquisition; rough set theory; attribute value reduction algorithm; decision-making system; knowledge acquisition; reduced decision table; rough sets theory; Algorithm design and analysis; Data mining; Decision making; Educational institutions; Frequency conversion; Information systems; Knowledge acquisition; Knowledge management; Rough sets; Uncertainty;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Knowledge Acquisition and Modeling, 2008. KAM '08. International Symposium on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-0-7695-3488-6
  • Type

    conf

  • DOI
    10.1109/KAM.2008.170
  • Filename
    4732804