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Constraint-Preserving Architecture Transformations:A Graph Rewriting Appraoch
作者姓名:王珏  王驹
作者单位:WANG Jue WANG Ju Institute of Software,The Chinese Academy of Sciences,Beijing 100080,P.R. China E-mail: wangj @iamail. ia. ar .cn Received June 19,2000; revised February 24,2001.
基金项目:This work is supported by the Nationa
摘    要:1 IntroductionIn Rough Set Theory1], Pawall has defined two sorts of infOrInion systems withoat and withdecision attributes, denoted as (U C} and (U C U D) respectthely Rere U is the forrse Of obects,Me C and D aJre the condition attribote set tal the decision attriliute set respectively Their reductsare called reduct and rel8Jtive reduct reSPecttwBy Pawha, a reduct must satisfy a indePendent conditbo, tha is, a reduct 0 / R G C, R is'independent if Vr C R, mD(R) / mD(R-- {r}) f…


Reduction Algorithms Based on Discernibility Matrix: The Ordered Attributes Method
WANG Jue WANG Ju Institute of Software,The Chinese Academy of Sciences,Beijing ,P.R. China E-mail: wangj @iamail. ia. ar .cn Received June , revised February ,..Constraint-Preserving Architecture Transformations:A Graph Rewriting Appraoch[J].Journal of Computer Science and Technology,2001,16(6):0-0.
Authors:WANG Jue WANG Ju Institute of Software  The Chinese Academy of Sciences  Beijing  PR China E-mail: wangj @iamail ia ar cn Received June    revised February  
Affiliation:WANG Jue WANG Ju Institute of Software,The Chinese Academy of Sciences,Beijing 100080,P.R. China E-mail: wangj @iamail. ia. ar .cn Received June 19,2000, revised February 24,2001.
Abstract:In this paper, we present reduction algorithms based on the principle of Skowron's discernibility matrix - the ordered attributes method. The completeness of the algorithms for Pawlak reduct and the uniqueness for a given order of the attributes are proved. Since a discernibility matrix requires the size of the memory of U2, U is a universe of objects, it would be impossible to apply these algorithms directly to a massive object set. In order to solve the problem, a so-called quasi-discernibility matrix and two reduction algorithms are proposed. Although the proposed algorithms are incomplete for Pawlak reduct, their opimal paradigms ensure the completeness as long as they satisfy some conditions. Finally we consider the problem on the reduction of distributive object sets.
Keywords:rough set theory  principle of discernibility matrix  inductive machine learning  
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