[Objective] In order to find synonymous relations for knowledge organization system integration. [Methods] This paper presents an automatic algorithm, which consists of lemmatization and semantic merging, as well as various methods to control the effects induced by vocabulary granularity. [Results] Its efficiency and effectiveness is well demonstrated from large scale data testing using many source vocabularies, compared with well-known integrated knowledge organization system. [Conclusions] The proposed algorithm can be used in large scale knowledge organization system integration, and is helpful for Chinese knowledge organization system integration.
李晓瑛, 李丹亚, 钱庆, 孙海霞, 李军莲, 胡铁军. 面向知识组织系统整合的英文同义关系自动发现算法研究*[J]. 现代图书情报技术, 2014, 30(5): 26-32.
Li Xiaoying, Li Danya, Qian Qing, Sun Haixia, Li Junlian, Hu Tiejun. Research on Automatic Algorithm of Finding English Synonymous Relations for Knowledge Organization System Integration. New Technology of Library and Information Service, DOI：10.11925/infotech.1003-3513.2014.05.04.
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