提出一种语义贴近度算法，并通过定量计算获得不同本体的语义贴近度，提供了面向本体应用的决策依据；
Described in detail the algorithms of semantic proximity, and calculated the semantic proximity of different ontology to offer decision-making basis that ontology uses.
最后，根据可分层术语集合的特性，证明了循环不动点理论在本体知识库下可用于计算可分层术语集合的语义模型。
Finally, this thesis proves that the recursion fixed point theory can also be used for the semantic model computation of a stratified TBox in ontology knowledge base.
针对当前本体搜索中存在的问题，提出了一种通过拆分概念来获取语义关键词进而通过计算权值来获得一组本体特征指数的方法。
The method of unfolding concepts of ontology to get a set of keywords with semantics and then computing the weight-value of the keywords to acquire the ontology index is proposed in this paper.
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