Title :
Research on Inductive Knowledge Acquisition Method and Application Based on Graph Analysis
Author :
Wulamu, Aziguli ; Hongyun, Chen
Author_Institution :
Sch. of Inf. Eng., Univ. of Sci. & Technol. Beijing, Beijing, China
Abstract :
Inductive learning is one of the basic cognitive skills in experiential knowledge acquisition. The consistency of inductive logic and inductive learning in research objects and methods make it possible to form inductive technique by specification on theories and methods of inductive logic on basis of cognitive mechanics. In this paper, by combining inductive logic theory and graph theory of Shindika´s probability logic system with inductive learning, a new graph-based learning algorithm is proposed and the corresponding machine learning system is built, and then the validity is verified by applying knowledge acquisition to slope stability analysis in mine engineering case.
Keywords :
graph theory; knowledge acquisition; learning by example; probabilistic logic; graph analysis; inductive knowledge acquisition; inductive learning; inductive logic; mine engineering case; probability logic system; Algorithm design and analysis; Friction; Knowledge acquisition; Knowledge based systems; Machine learning; Numerical stability; Stability analysis; Graph Theory; Inductive Logic; Knowledge Acquisition; Slope Stability;
Conference_Titel :
Computational and Information Sciences (ICCIS), 2010 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-8814-8
Electronic_ISBN :
978-0-7695-4270-6
DOI :
10.1109/ICCIS.2010.295
