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一种基于约束依赖性分析的RDFS模式抽取方法
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[J]. 软件学报, 2020, 31(2): 344-355
作者姓名:赵晓非  史忠植  田东平  刘建伟
作者单位:天津工业大学计算机科学与技术学院,天津300387;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;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
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)
摘    要:

收稿时间:2018-01-31
修稿时间:2018-05-01

RDFS Schema Extracting Method Based on Analysis of Constraint Dependency
ZHAO Xiao-Fei,SHI Zhong-Zhi,TIAN Dong-Ping and LIU Jian-Wei. RDFS Schema Extracting Method Based on Analysis of Constraint Dependency[J]. Journal of Software, 2020, 31(2): 344-355
Authors:ZHAO Xiao-Fei  SHI Zhong-Zhi  TIAN Dong-Ping  LIU Jian-Wei
Affiliation:School of Computer Science and Technology, Tianjin Polytechnic University, Tianjin 300387, China;Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China,Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China,Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China and 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.
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