机构知识库语义知识获取方法分析及实验研究

Analysis and Experimental Research on Method of Semantic Knowledge Acquisition for Institutional Repository

【目的】通过分析总结和实验研究,提出并形成一种有效的语义知识获取方法,为实现机构知识库的语义化提供理论基础和可行技术路线。【方法】对国内外的语义知识获取方法进行对比分析,提出机构知识库语义知识获取的体系框架,并总结和深度解析其关键技术;同时,以中国科学院机构知识库平台为例进行实验研究。【结果】该方法可有效地从机构知识库底层的关系数据库的数据和实体关系结构中自动获取语义知识信息并转化为RDF三元组形式进行浏览和查询。【局限】定义一个合理有效的语义映射规则,需要经过领域专家评估、较多的人工干预以及反复实验才能确定;不同机构知识库间同一实体对象的语义知识获取关联没有涉及。【结论】有利于帮助后续研究人员和机构知识库开发人员更好地了解和掌握机构知识库语义知识获取的方法和关键技术,从而为提升机构知识库的服务能力奠定基础。

[Objective] The paper proposes and forms an effective method of semantic knowledge acquisition through analysis, summary and experiment, in order to provide theoretical principle and possible technological route for the semantization of Institutional Repository. [Methods] Based on the contrastive analysis of methods of semantic knowledge acquisition both at home and abroad, the paper proposes a system framework of semantic knowledge acquisition for Institutional Repository, and sums up its key technologies for deep analysis and then takes the CAS IR GRID for an experimental study. [Results] This method can automatically and effectively acquire semantic knowledge information from data and entity relationship structure of relational database of underlying Institutional Repository and convert it into RDF triples for browse and search. [Limitations] To define a reasonable and effective mapping rule may need domain expert evaluation, more manual intervention and repeated experiments. The semantic knowledge acquisition and relevance study for the same entity object between different Institutional Repository is not involved in this paper. [Conclusions] This study may better help follow-up researchers and developers quickly understand and master the method and key technologies of semantic knowledge acquisition, then lay the foundations for enhancing knowledge service capabilities of Institutional Repository.