为了支持语义网对不精确性知识的机器理解与机器推理,提出了不精确性语义网本体的设想.通过分析"不精确性"和"概念"的语义,界定不精确性包括模糊性和粗糙性,其分别源于人脑形成概念时所采用的圈定方式和导出方式,进而指出不精确性概念实际上就是模糊粗糙概念,而不精确性偏序关系并不实际存在,由此推证出不精确性语义网本体的集合表达式模型即模糊粗糙概念偏序集.给出了该模型的两种实用性表示形式:模糊粗糙概念表和模糊粗糙概念格,后者具有约简性和惟一性的良好性质,据此可编写简洁规范的OWL文档,从而支持语义网的实际运行.%To support the semantic web to implement the machine understanding and machine reasoning of the imprecise knowledge,the idea of imprecise semantic web ontology is presented. By analyzing the semantic meaning of the imprecision and the concept, it is concluded that the imprecision includes the fuzziness and the roughness, which respectively come from the enclosing type and the educing type adopted for forming a concept in human brain. The imprecise concept is actually the fuzzy rough concept, but there is no existence ofthe imprecise partial ordering relation actually. Asetexpressionmodel of imprecisesemanticwebontologyisderived, and it is actuaily a fuzzy rough concept partial ordering set. This model could be represented as two types of applied forms: the fuzzy rough concept list and the fuzzy rough concept lattice, the latter has good properties with compactness and exclusiveness, so it could be as a base to code a compact and normative OWL document which helps the semantic web to come true.
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