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Integrating Bipolar Fuzzy Mathematical Morphology in Description Logics for Spatial Reasoning

机译:在描述逻辑中集成双极模糊数学形态进行空间推理

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Bipolarity is an important feature of spatial information, involved in the expression of preferences and constraints about spatial positioning or in pairs of opposite spatial relations such as left and right. Another important feature is imprecision which has to be taken into account to model vagueness, inherent to many spatial relations (as for instance vague expressions such as close to, to the right of), and to gain in robustness in the representations. In previous works, we have shown that fuzzy sets and fuzzy mathematical morphology are appropriate frameworks, on the one hand, to represent bipolarity and imprecision of spatial relations and, on the other hand, to combine qualitative and quantitative reasoning in description logics extended with fuzzy concrete domains. The purpose of this paper is to integrate the bipolarity feature in the latter logical framework based on bipolar and fuzzy mathematical morphology and description logics with fuzzy concrete domains. Two important issues are addressed in this paper: the modeling of the bipolarity of spatial relations at the terminological level and the integration of bipolar notions in fuzzy description logics. At last, we illustrate the potential of the proposed formalism for spatial reasoning on a simple example in brain imaging.
机译:双极性是空间信息的重要特征,涉及关于空间定位的偏好和约束的偏好和约束,或成对的相反空间关系,例如左右。另一个重要特征是不确定,这必须考虑到模拟模糊性,所固有的空间关系(例如模糊表达,例如靠近右侧),并在表示中获得鲁棒性。在以前的作品中,我们已经表明,模糊集和模糊数学形态是适当的框架,一方面代表空间关系的跨度和不精确,另一方面,以模糊的描述逻辑中的定性和定量推理。混凝土域。本文的目的是基于双极和模糊数学形态和描述具有模糊混凝土域的后者逻辑框架中的双极特征集成了双极性特征。本文讨论了两个重要问题:术语水平术语水平在术语水平上的跨越跨度的建模和模糊描述逻辑中双极概念的集成。最后,我们说明了拟议的形式主义在脑成像中的一个简单示例中的空间推理的潜力。

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