融合概念格约简的中文领域本体学习方法

在基于形式概念分析的中文领域本体学习中，为提高概念格构建效率，将概念格约简理论应用于概念格构建中。首先对基于语义依存分析获取的形式背景进行对象和属性约简，然后基于约简的形式背景采用Godin算法构造概念格，最后根据修复定理修复约简概念格，得到完整的概念格。通过有关对萝蘼科植物的文本学习，得到一个萝蓐科植物领域本体。实验结果表明，引入概念格约简理论，概念格的构建效率提高70％，进而提高了领域本体构建的效率。

Concept Lattice Reduction Application in Field of Chinese Domain Ontology Learning

In order to improve the efficiency of building concept lattice in Chinese domain ontology learning based on formal concept analysis, we applied the concept lattice reduction theory to the process of building concept lattice. The main idea is that we reduce the objects and attributes of the obtained formal context which is based on semantic dependency analysis, adopte the Godin algorithm to construct concept lattice based on formal context reduced, and repaire the concept lattice with the reparation theories. The article takes the asclepiadaceae plants ontology construction as an example to verify this method. The experiment results show that the efficiency of concept lattice construction increase by 70%. It improves the efficiency of ontology construction.