引用本文:赵晓非,史忠植,田东平,刘建伟.一种基于约束依赖性分析的RDFS模式抽取方法.软件学报,2020,31(2):344-355
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一种基于约束依赖性分析的RDFS模式抽取方法
赵晓非1,2, 史忠植2, 田东平2, 刘建伟2
1.天津工业大学 计算机科学与技术学院, 天津 300387;2.中国科学院 计算技术研究所 智能信息处理重点实验室, 北京 100190
摘要:
为了验证RDFS(resource description framework schema)本体的正确性所执行的推理是一项计算开销很大的任务,该任务在附加约束存在的条件下变得更加复杂.提出了一种旨在不改变推理结果的前提下,对RDFS模式进行抽取的方法.该方法基于对约束间的依赖关系进行分析.为了获取RDFS模式的精确语义,首先,将模式元素和约束形式化为一阶谓词逻辑中的析取嵌入依赖;接着,根据约束间的相互影响建立约束依赖图,在此基础上,提出了删除与推理任务无关的边和节点的策略;最后,通过重构造过程获取RDFS子模式.该方法使得推理验证可以在抽取后的小规模本体上进行.实验结果显示,该方法可以显著地提高RDFS本体验证过程的效率,抽取过程的平均耗时为0.60s,与推理检测时间相比几乎可以忽略,而获得的效率提升则为2.00倍~22.97倍不等.
关键词:  RDFS(resource description framework schema)  约束  本体抽取  依赖性分析
DOI:10.13328/j.cnki.jos.005614
分类号:TP182
基金项目:国家重点基础研究发展计划(973)(2013CB329502);国家自然科学基金(61035003);江苏省计算机信息处理技术重点实验室开放基金(KJS1737);陕西省科技厅工业攻关项目(2018GY-037)
RDFS Schema Extracting Method Based on Analysis of Constraint Dependency
ZHAO Xiao-Fei1,2, SHI Zhong-Zhi2, TIAN Dong-Ping2, LIU Jian-Wei2
1.School of Computer Science and Technology, Tianjin Polytechnic University, Tianjin 300387, China;2.Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China
Abstract:
The reasoning performed to verify the correctness of the RDFS ontologies is the task with high computational cost. The task will become more complex in the scenario of existence of additional constraints. This paper presents an approach that can extract the RDFS schema without changing the reasoning results. This approach is based on the analysis of the dependency relationships between the constraints. To capture the precise semantics of the RDFS schema, firstly, the schema elements and the constraints are formalized into first-order formulas expressed as disjunctive embedded dependencies and the constraint depandency graph is established according to the interaction between the constraints. Then, the strategies for deleting the edges and the nodes that are irrelevant to the reasoning tasks are applied. Finally, the RDFS sub-schema is obtained through the reconstruction process. The proposed approach enables the reasoning to be carried out on the extracted small-scale ontologies. The experiment results show that the proposed approach can significantly improve the efficiency of the RDFS ontology validation. Compared to the reasoning time, the average time (0.60s) consumed by the extraction process is almost negligible, while the efficiency increasement ranges from 2.00 times to 22.97 times.
Key words:  RDFS (resource description framework schema)  constraint  ontology extracting  dependency analysis

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