A heuristic algorithm based on conditional information entropy for knowledge reduction is proposed, and the complexity of this algorithm is analyzed.
提出了一种基于条件信息熵的知识约简启发式算法，并指出该算法的时间复杂度是多项式的。
The concept of rough entropy is proposed. The monotony between the uncertainty of knowledge in the rough set theory and its corresponding rough entropy is proved.
提出了粗糙信息熵的概念，证明了粗糙集理论中知识不确定性与其所对应的粗糙信息熵之间的单调关系。
Information storage, entropy and connotation reflect three guidelines of an enterprise, that is, inner knowledge capacity, systematic sequence and content.
知识存量、信息熵、知识语义是反映企业内部知识容量，系统有序性以及内容的三个指标。
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