基于结构特征量化的本体模块化划分研究

针对大规模本体模块化划分问题，从本体结构与复杂网络的相似性分析入手，根据本体语义和网络结构特征将其转换为对应的概念网络。提出衡量本体中节点局部中心度和边的语义连接强度的量化标准，用于选取核心节点和度量边权重，得到显式表示本体语义和结构特征的无向加权层次网络，将其建模为具有不同位势的电路网络，利用最大位势差法划分本体模块。实验结果表明，该方法能够在线性时间内得到质量较高、适合匹配应用的本体划分。

Research of Ontology Modular Partition Based on Structure Characteristics Quantitation

As for large-scale ontology modular partition problem,this paper analyzes the similarity between complex networks and ontology structure,converts ontology to the corresponding concept networks according to its semantic and structural characteristics.It proposes a set of quantitative criteria for measuring the local central of nodes and semantic connection strength of edges,uses these quantitative criteria to identify core concept nodes and assign weight to edges,obtains undirected weighted hierarchical networks,which explicit express ontology semantic and structural characteristics,transforms the networks to circuit voltage networks,and partitions it by the maximum potential difference method.Experimental results show that this method can acquire high-quality ontology modules in linear time and fit for the further use of ontology matching application.