Measures of uncertainty for knowledge bases

This paper investigates measures of uncertainty for knowledge bases by using their knowledge structures. Knowledge structures of knowledge bases are first introduced. Then, dependence and independence between knowledge structures of knowledge bases are proposed, which are characterized by inclusion degree. Next, measures of uncertainty for a given knowledge base are studied, and it is proved that the proposed measures are based on the knowledge structure of this knowledge base. Finally, a numerical experiment is conducted to show performance of the proposed measures and effectiveness analysis is done from two aspects of dispersion and correlation in statistics. These results will be significant for understanding the essence of uncertainty for knowledge bases.

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