DocumentCode
511284
Title
Research on Cognitive Induction Based Knowledge Acquisition
Author
Dezheng, Zhang ; Aziguli ; Hongyun, Chen
Author_Institution
Inst. of Inf. Eng., Beijing Univ. of Sci. & Technol., Beijing, China
Volume
1
fYear
2009
fDate
25-27 Dec. 2009
Firstpage
227
Lastpage
234
Abstract
Modern Inductive Logic is an important component in inductive learning logic, which is one of the basic cognitive skills in experience knowledge acquisition. The consistency of inductive logic and inductive learning in research object and method make it possible to form inductive technique by specification on theories and methods of inductive logic on basis of cognitive mechanics. The difference between Inductive Logic and Inductive Learning in the research aim determines we should not copy the theories of Inductive Logic and should rest on Artificial intelligence and do some appropriate quotations from the theories of Modern Inductive Logic. In this paper, by combing inductive logic theory of Shindika´s probability logic System with inductive learning technique, a new learning algorithm is proposed and the corresponding machine learning system is built, and then the validity is verified by clinical cases Traditional Chinese Medicine (TCM).
Keywords
cognitive systems; knowledge acquisition; learning by example; probabilistic logic; Shindika probability logic system; artificial intelligence; basic cognitive skills; cognitive induction; cognitive mechanics; inductive learning logic; inductive logic theory; knowledge acquisition; machine learning system; modern inductive logic; traditional chinese medicine; Application software; Artificial intelligence; Cognition; Computer applications; Knowledge acquisition; Knowledge engineering; Machine learning; Machine learning algorithms; Probabilistic logic; Utility theory; Cognition; Component; Confirmation; Inductive Logic; Knowledge Acquisition;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science-Technology and Applications, 2009. IFCSTA '09. International Forum on
Conference_Location
Chongqing
Print_ISBN
978-0-7695-3930-0
Electronic_ISBN
978-1-4244-5423-5
Type
conf
DOI
10.1109/IFCSTA.2009.62
Filename
5385093
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