一种基于约束依赖性分析的RDFS模式抽取方法
作者:
作者单位:

作者简介:

赵晓非(1978-),男,辽宁黑山人,博士,副教授,主要研究领域为语义Web,分布智能;田东平(1981-),男,博士,副教授,主要研究领域为语义Web,人工智能;史忠植(1941-),男,研究员,博士生导师,CCF会士,主要研究领域为人工智能,语义Web,机器学习;刘建伟(1979-),女,讲师,主要研究领域为本体工程,语义Web.

通讯作者:

赵晓非,E-mail:zhaoxiaofei1978@hotmail.com

中图分类号:

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
Author:
Affiliation:

Fund Project:

National Basic Research Program of China (973) (2013CB329502); National Natural Science Foundation of China (61035003); Open Foundation of Jiangsu Provincial Key Laboratory for Computer Information Processing Technology (KJS1737); Industrial Research Project of Science and Technology Bureau, Shaanxi Province (2018GY-037)

  • 摘要
  • |
  • 图/表
  • |
  • 访问统计
  • |
  • 参考文献
  • |
  • 相似文献
  • |
  • 引证文献
  • |
  • 资源附件
  • |
  • 文章评论
    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.

    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.

    参考文献
    相似文献
    引证文献
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

复制
分享
文章指标
  • 点击次数:
  • 下载次数:
  • HTML阅读次数:
  • 引用次数:
历史
  • 收稿日期:2018-01-31
  • 最后修改日期:2018-05-01
  • 录用日期:
  • 在线发布日期: 2020-02-17
  • 出版日期: 2020-02-06
您是第位访问者
版权所有:中国科学院软件研究所 京ICP备05046678号-3
地址:北京市海淀区中关村南四街4号,邮政编码:100190
电话:010-62562563 传真:010-62562533 Email:jos@iscas.ac.cn
技术支持:北京勤云科技发展有限公司

京公网安备 11040202500063号