Title :
Granular computing on covering from the aspects of knowledge theory
Author :
Barot, Rushin B. ; Lin, T.Y.
Author_Institution :
San Jose State Univ., San Jose, CA
Abstract :
Rough Set theory assumes the underlying structure of knowledge is a partition; each equivalence class represents a piece of basic knowledge. In this paper, we assumes a covering is a basic knowledge. From which the theories of learning, knowledge approximations and knowledge reduction are developed.
Keywords :
approximation theory; equivalence classes; learning (artificial intelligence); rough set theory; equivalence class; granular computing; knowledge approximation; knowledge reduction; learning theory; rough set theory; Approximation methods; Computer science; Set theory;
Conference_Titel :
Fuzzy Information Processing Society, 2008. NAFIPS 2008. Annual Meeting of the North American
Conference_Location :
New York City, NY
Print_ISBN :
978-1-4244-2351-4
Electronic_ISBN :
978-1-4244-2352-1
DOI :
10.1109/NAFIPS.2008.4531346
