Rough set extensions in incomplete information systems

All eight possible extended rough set models in incomplete information systems are proposed. By analyzing existing extended models and technical methods of rough set theory, the strategy of model extension is found to be suitable for processing incomplete information systems instead of filling possible values for missing attributes. After analyzing the definitions of existing extended models, a new general extended model is proposed. The new model is a generalization of indiscernibility relations, tolerance relations and nonsymmetric similarity relations. Finally, suggestions for further study of rough set theory in incomplete information systems are put forward.

[1]  L. Zadeh,et al.  Fuzzy Logic for the Management of Uncertainty , 1992 .

[2]  Jerzy W. Grzymala-Busse,et al.  LERS-A System for Learning from Examples Based on Rough Sets , 1992, Intelligent Decision Support.

[3]  Zdzisław Pawlak,et al.  Rough sets: a new approach to vagueness , 1992 .

[4]  R. Słowiński.  Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory , 1992 .

[5]  Wojciech Ziarko,et al.  Variable Precision Rough Set Model , 1993, J. Comput. Syst. Sci..

[6]  Jerzy W. Grzymala-Busse,et al.  Rough Sets , 1995, Commun. ACM.

[7]  Marzena Kryszkiewicz,et al.  Rough Set Approach to Incomplete Information Systems , 1998, Inf. Sci..

[8]  Alexis Tsoukiàs,et al.  On the Extension of Rough Sets under Incomplete Information , 1999, RSFDGrC.

[9]  Marzena Kryszkiewicz,et al.  Probabilistic Approach to Association Rules in Incomplete Databases , 2000, Web-Age Information Management.

[10]  Alexis Tsoukiàs,et al.  Valued Tolerance and Decision Rules , 2000, Rough Sets and Current Trends in Computing.

[11]  Jerzy W. Grzymala-Busse,et al.  A Comparison of Several Approaches to Missing Attribute Values in Data Mining , 2000, Rough Sets and Current Trends in Computing.

[12]  Alexis Tsoukiàs,et al.  Incomplete Information Tables and Rough Classification , 2001, Comput. Intell..

[13]  Guoyin Wang,et al.  Extension of rough set under incomplete information systems , 2002, 2002 IEEE World Congress on Computational Intelligence. 2002 IEEE International Conference on Fuzzy Systems. FUZZ-IEEE'02. Proceedings (Cat. No.02CH37291).

[14]  Jerzy W. Grzymala-Busse,et al.  A Rough Set Approach to Data with Missing Attribute Values , 2006, RSKT.

[15]  Wang,et al.  Domain-Oriented Data-Driven Data Mining Based on Rough Sets , 2006 .

[16]  Jerzy W. Grzymala-Busse,et al.  Rough Set Strategies to Data with Missing Attribute Values , 2006, Foundations and Novel Approaches in Data Mining.