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Reasoning with Uncertain Information and Trust

机译:具有不确定信息和信任的推理

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A limitation of standard Description Logics is its inability to reason with uncertain and vague knowledge. Although probabilistic and fuzzy extensions of DLs exist, which provide an explicit representation of uncertainty, they do not provide an explicit means for reasoning about second order uncertainty. Dempster-Shafer theory of evidence (DST) overcomes this weakness and provides means to fuse and reason about uncertain information. In this paper, we combine DL-Lite with DST to allow scalable reasoning over uncertain semantic knowledge bases. Furthermore, our formalism allows for the detection of conflicts between the fused information and domain constraints. Finally, we propose methods to resolve such conflicts through trust revision by exploiting evidence regarding the information sources. The effectiveness of the proposed approaches is shown through simulations under various settings.
机译:标准描述逻辑的局限性在于无法以不确定和模糊的知识进行推理。尽管存在DL的概率扩展和模糊扩展,它们提供了不确定性的明确表示,但它们并没有提供推理二阶不确定性的明确方法。 Dempster-Shafer证据理论(DST)克服了这一弱点,并提供了融合和推理不确定信息的手段。在本文中,我们将DL-Lite与DST结合使用,可以对不确定的语义知识库进行可扩展的推理。此外,我们的形式主义允许检测融合信息与域约束之间的冲突。最后,我们提出了利用有关信息源的证据通过信任修订来解决此类冲突的方法。通过在各种设置下的仿真显示了所提出方法的有效性。

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