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UM E-Theses Collection (澳門大學電子學位論文庫)

Title

Hybrid knowledge-based support with learning abilities

English Abstract

Abstract Hybrid knowledge-based support is based on a combination of following paradigms; Case-based reasoning (CBR), Rule-based reasoning, and several others. CBR is a problem solving paradigm by matching current problem against problems solved successfully in the past. The process can be augmented by adapting solutions. Learning process of a CBR, CBR adaptation can be supported by incorporating adaptation rule bases and data mining methods. This presented research investigates application of CBR and data mining methods on several problem domains. Development of adaptation rule base for CBR adaptation process is also discussed in detail. Framework for integration of data mining methods into CBR is described. This framework is further generalized by incorporating it into Knowledge Discovery Support Environment (KDSE).

Issue date

1997.

Author

Maung, Aung Soe Paing

Faculty

Faculty of Science and Technology

Department

Department of Computer and Information Science

Degree

M.Sc.

Subject

Expert systems (Computer science)

Case-based reasoning

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Location
1/F Zone C
Library URL
991000173029706306