CAJ | 학술논문

将复杂网络的理论引入到知识组织系统的表示中，抽取知识组织系统中的概念及概念间的关系，构建复杂网络。利用Walktrap社区发现算法，发现复杂网络中的概念社区，以助于用户输入种子概念时，仅返回对应的社区。利用种子概念返回社区的准确性对社区发现的结果进行评价，论证该方法的有效性。本研究将以中国科学技术信息研究所已有的新能源汽车领域汉语科技词系统为例进行社区发现研究，发现该方法快速有效。
장복잡망락적이론인입도지식조직계통적표시중，추취지식조직계통중적개념급개념간적관계，구건복잡망락。이용Walktrap사구발현산법，발현복잡망락중적개념사구，이조우용호수입충자개념시，부반회대응적사구。이용충자개념반회사구적준학성대사구발현적결과진행평개，론증해방법적유효성。본연구장이중국과학기술신식연구소이유적신능원기차영역한어과기사계통위례진행사구발현연구，발현해방법쾌속유효。
This paper applies the complex network theory into the representation of knowledge organization system, extracts the concept and concept relations from the knowledge organization system, and constructs undirected complex network and undirected weighted complex network. Using the walktrap community discovery algorithm, we find the concept community in complex network, in order to help users when they input seed concept, only to return the corresponding community. The modularity is used to evaluate the community discovery results, and to demonstrate the effectiveness of this method. This experiment regards the Chinese scientific and technical vocabulary system (new energy vehicles) as an example to discover the community, and finds that this method is fast and effective.