2007Microelectronics & ComputerRequires access

Research on the Extended Relations in Incomplete Information System

Lin Shang

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Abstract

The classical rough set theory is based on complete information systems.In order to process incomplete information systems,the classical rough set theory needs to be extended.In this paper,several extension relations based on rough set under incomplete information are discussed.A constrained similarity relation as a new extension of rough sets theory is introduced,and the concepts of the positive region,accuracy of approximation,quality of approximation and dependency of attributes defined on constrained similarity relation are proposed.

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What this paper is about

The classical rough set theory is based on complete information systems.In order to process incomplete information systems,the classical rough set theory needs to be extended.In this paper,several extension relations based on rough set under incomplete information are discussed.A constrained similarity relation as a new extension of rough sets theory is introduced,and the concepts of the positive region,accuracy of approximation,quality of approximation and dependency of attributes defined on constrained similarity relation are proposed.

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Available abstract

The classical rough set theory is based on complete information systems.In order to process incomplete information systems,the classical rough set theory needs to be extended.In this paper,several extension relations based on rough set under incomplete information are discussed.A constrained similarity relation as a new extension of rough sets theory is introduced,and the concepts of the positive region,accuracy of approximation,quality of approximation and dependency of attributes defined on constrained similarity relation are proposed.

Key concepts: Rough set, Computer science, Extension (predicate logic), Similarity (geometry), Relation (database), Dependency (UML), Dominance-based rough set approach, Set (abstract data type)

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