基于主题词表与百科知识相融合的领域本体自动构建研究  

Automatic Modeling of Large-Scale Domain Ontology Based on Thesauruses and Online Encyclopedias

作　　者：王汀[1] 冀付军[1] 

机构地区：[1]首都经济贸易大学信息学院,北京100070

出　　处：《情报学报》2017年第7期723-733,共11页Journal of the China Society for Scientific and Technical Information

基　　金：国家社会科学基金青年项目"网游沉溺机制研究"(13CXW057)

摘　　要：在进行大规模领域本体的构建时,基于手工方式的构建模式效率较低并且可行性较差。为了解决大规模领域本体的自动化构建问题,提出了一种领域主题词表与网络百科知识库相融合的两阶段领域本体自动化构建方案。第一阶段,进行主题词表至本体的粗映射,形成领域粗糙本体;第二阶段,采用改进的同义词词林与编辑距离相似度相结合的方式对百科知识与粗糙本体进行自动融合、自适应调整和扩充,形成含有丰富语义信息的、良构的领域本体。基于两阶段方法自动化地构建了大规模中国电子政务领域本体(Chinese E-Gov Ontology),从而验证该方法的可行性和有效性。While constructing a large-scale domain ontology, the traditional manual construction method has low effi- ciency and feasibility. In order to solve the large-scale domain ontology automatic building problem, making use of the cross-domain coverage characteristics of the Chinese online encyclopedia and the e-government thesaurus, based on the improved TongYiCiCiLin similarity computing algorithms, this paper puts forward a two-stage automatic con- structing ontology solution by merging the domain thesaurus and online encyclopedia knowledge base together. Based on the proposed approach, this paper takes the Chinese e-government domain as an example and automatically builds a large-scale ontology as the foundation of Chinese Linked Open Government Data construction. Practice proves that the system has feasibility and robustness in achieving the goal of rapid and automatic building of large-scale domain ontology.

关 键 词：领域本体 主题词表 两阶段方法 本体学习 关联数据 

分 类 号：TP391.1[自动化与计算机技术—计算机应用技术]