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A Fuzzy Description Logic Based Spatial Direction Reasoning Approach

机译:基于模糊描述逻辑的空间方向推理方法

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In order to solve the problem of existing spatial cardinal direction relation expression models which have disadvantage to capture imprecision and fuzziness, the fuzzy description logic and fuzzy rules are introduced into the expression of cardinal direction relation. Fuzzy rules based reasoning approach is proposed to strengthen of imprecision and fuzziness of processing and analyzing ability. In that way, the representing of fuzzy and crisp relations between fuzzy regions or crisp regions can be unified in one formal framework. In the implementa-tion, on the one hand, fuzzy rules are used to rewrite the existing spatial reasoning rule. All rules used in this paper are independent of spe-cific issues, that is to say, all the cardinal direction reasoning are using the same set of rules. On the other hand, the existing annotation of OWL2 is used to realize fuzzy ontology. No new label is extended into OWL2 language. Therefore, there is no need to develop a new rea-soning tool or plugin. There is also no need to prove the correctness of our approach. For reasoning about cardinal relations between fuzzy regions, some approximate methods are used. The experiment results show that the recall ratio of the results is 86.4% when two fuzzy re-gions are used.
机译:为了解决现有的空间基向关系表达模型存在捕获不精确和模糊性的缺点,将模糊描述逻辑和模糊规则引入基向关系表达中。提出了基于模糊规则的推理方法,以增强处理和分析能力的不精确性和模糊性。这样,就可以在一个正式框架中统一表示模糊区域或清晰区域之间的模糊和清晰关系。在实现中,一方面,使用模糊规则来重写现有的空间推理规则。本文使用的所有规则都与特定问题无关,也就是说,所有基本方向推理都使用相同的规则集。另一方面,OWL2的现有注释用于实现模糊本体。没有新标签扩展到OWL2语言。因此,无需开发新的推理工具或插件。也没有必要证明我们方法的正确性。为了推理模糊区域之间的基数关系,使用了一些近似方法。实验结果表明,当使用两个模糊区域时,结果的查全率是86.4%。

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