Title :
Research on Method of Case Base Data Mining Learning Based on Rough Set
Author :
Li, Jingwei ; Song, Dong
Author_Institution :
Sch. of Aeronaut., Northwestern Polytech. Univ., Xi´´an, China
Abstract :
Data mining based on rough set is introduced into CBR (Case-based Reasoning) system. And learning model of case base is established. The potential knowledge of case base is obtained and studied, through attribute reduction and attribute value reduction. Meanwhile, the structure and performance of case base is maintained and improved, through case reduction. The establishment of case base learning model raises the automaticity of knowledge acquisition and promotes the development of the CBR system positively. Then the process of learning is applied in the case base of fault diagnosis expert system of aircraft.
Keywords :
case-based reasoning; data mining; expert systems; fault diagnosis; rough set theory; CBR system; aircraft fault diagnosis expert system; attribute reduction; attribute value reduction; case base data mining learning; case base learning model; case reduction; case-based reasoning; rough set; Aircraft; Atmospheric modeling; Cognition; Computational modeling; Data mining; Fault diagnosis; Indexes;
Conference_Titel :
Computational Intelligence and Software Engineering (CiSE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5391-7
Electronic_ISBN :
978-1-4244-5392-4
DOI :
10.1109/CISE.2010.5676958