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Centralized Reasoning Translation and Its Computing Complexity for Heterogeneous Semantic Mappings

机译:异构语义映射的集中推理翻译及其计算复杂性

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Bridge rules provide an important mechanism for describing semantic mapping and propagating knowledge for distributed dynamic description logics (D3L). The current research focuses on the homogeneous bridge rules that only contain atomic elements. In this paper, the research is extended to the D3L reasoning problem with heterogeneous bridge rules that contain composite elements in subset ends. The regularity of the distributed knowledge base is defined. Through the alteration of the bridge rules and transforming different forms into existing language mechanisms, we present an algorithm that can convert the D3L knowledge base with dynamic description logic DSROIQ as the local ontology language into a single DSROIQ knowledge base. Next, we study the properties of the algorithm. We prove that the algorithm will terminate in polynomial time and that 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 the regular D3L knowledge base with such bridge rules is the same as that on a single DSROIQ knowledge base. The method proposed in this paper makes centralized reasoning for D3L obtain the same worst-case time complexity as the existing distributed reasoning method and solves the problem that the latter cannot handle heterogeneous composite bridge rules.
机译:桥规则为描述语义映射和传播分布式动态描述逻辑(D3L)的知识提供了一种重要的机制。当前的研究集中于仅包含原子元素的齐次桥规则。本文将研究扩展到具有异构子集规则的D3L推理问题,该规则在子集末端包含复合元素。定义了分布式知识库的规则性。通过更改桥接规则并将不同形式转换为现有的语言机制,我们提出了一种算法,该算法可以将具有动态描述逻辑DSROIQ作为本地本体语言的D3L知识库转换为单个DSROIQ知识库。接下来,我们研究算法的属性。我们证明该算法将在多项式时间内终止,并且目标知识库的可满足性等于原始知识库的可满足性。因此,我们证明了在具有这种桥接规则的常规D3L知识库上,集中推理的最坏情况下的时间复杂度与在单个DSROIQ知识库上的集中推理的最坏情况下的时间复杂度相同。本文提出的方法使D3L的集中式推理获得与现有的分布式推理方法相同的最坏情况下的时间复杂度,并解决了后者无法处理异构复合桥规则的问题。

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