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Neighborhood modeling algorithm of geographic entity in natural language geocoding

机译:自然语言地理编码中地理实体的邻域建模算法

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Neighborhood Modeling lays the basis for natural language geocoding with neighborhood properties. With the deep analysis of research results of former scientists, and the special requirement of Geocoding, Observation scale, geometry shape of geographic entity and spatial distribution are selected as the key influencing factors for determining neighborhood range of geographic entities in natural language address. Then, based on consideration of above four key influencing factors, we model the neighborhood of geographic entity based on fuzzy set theory, and design several investigation tables about human beings neighborhood range cognition of singe line or face shape entity and multiple entities etc. According to the analysis of the test result, several formulas and algorithms were put forward to calculate the buffering distance of neighborhood range of different type of geographic entity. It is concluded that the neighborhood modeling algorithm proposed in this paper can be applied in future geocoding algorithm, because it faithfully fits cognition of human beings about the neighborhood concept in natural language address.
机译:邻域建模为具有邻域属性的自然语言地理编码奠定了基础。在对前任科学家的研究成果进行深入分析的基础上,结合地理编码的特殊要求,选择地理实体的观测尺度,几何形状和空间分布作为确定自然语言地址中地理实体邻域范围的关键影响因素。然后,在综合考虑上述四个主要影响因素的基础上,基于模糊集理论对地理实体的邻域进行建模,并设计了几张关于人类单线或人脸形状实体及多个实体的邻域范围认知的调查表。通过对测试结果的分析,提出了几种公式和算法来计算不同类型地理实体邻域范围的缓冲距离。结论是,本文提出的邻域建模算法可以真实地适应人类对自然语言地址中邻域概念的认知,因此可以应用于未来的地理编码算法中。

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