ISSN 1000-1239 CN 11-1777/TP

• 人工智能 •

面向异构语义映射的D3L转换算法及其性质研究

1. 1(天津工业大学计算机科学与软件学院 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);3(天津大学计算机科学与技术学院 天津 300072) (zhaoxiaofei1978@hotmail.com)
• 出版日期: 2018-12-01
• 基金资助:
国家“九七三”重点基础研究发展计划基金项目(2013CB329502)；国家自然科学基金项目(61035003)；江苏省计算机信息处理技术重点实验室开放基金项目(KJS1737);中国博士后科学基金项目(2018M631740)

Transformation Algorithm and Its Properties for D3L with Heterogeneous Semantic Mapping

Zhao Xiaofei1,2,3, Shi Zhongzhi2, Feng Zhiyong3

1. 1(School of Computer Science and Software Engineering, Tianjin Polytechnic University, Tianjin 300387);2(Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190);3(School of Computer Science and Technology, Tianjin University, Tianjin 300072)
• Online: 2018-12-01

Abstract: Bridge rules provide an important mechanism describing semantic mapping and propagating knowledge for D3L (distributed dynamic description logics). The current research focuses on the homogeneous bridge rules which only contain atomic elements. In this paper, the research is extended to the D3L reasoning problem with the heterogeneous bridge rules which contain composite elements in the contained end. The regularity of distributed knowledge base is defined. Through the alternation of the bridge rules and transforming different forms into existing language mechanism, we present a algorithm which can convert the D3L knowledge base with dynamic description logic DSROIQ as local ontology language into a single DSROIQ knowledge base. Then we study the properties of the algorithm. We prove that the algorithm will terminate in polynomial time and the satisfiability of the target knowledge base is equivalent to the satisfiability of the original knowledge base. Thus, we prove that the worst-case time complexity of the centralized reasoning on regular D3L knowledge base with such bridge rules is the same as that on single DSROIQ knowledge base. The method proposed in this paper makes the reasoning for D3L to obtain the same worst-case time complexity as the existing distributed reasoning methods and solves the problem that the latter can not handle heterogeneous composite bridge rules.