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Direction-Relation Similarity Model Based on Fuzzy Close-Degree

机译:基于模糊近距离的方向关系相似性模型

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Directional similarity is widely used in the assessment of spatial scene similarity and spatial query. Based on different representation models, direction-relation similarity models should be partitioned into quantitative and qualitative models. The traditional qualitative direction-relation similarity models based on directional matrix model assess the directional similarity by computing the least cost for transforming one directional matrix into another. These models are limited to be used in the directional matrices whose elements sum up to 1. This paper proposes a qualitative directional similarity computation model to evaluate the directional similarity, which is based on the schema of fuzzy close-degree. The new model ignores the relations between the cardinal directions and has a wide range application in the similarity assessment.
机译:方向相似度广泛用于空间场景相似性和空间查询的评估。基于不同的表示模型,方向关系相似性模型应分为定量和定性模型。基于定向矩阵模型的传统定性方向相似性模型通过计算将一个定向矩阵转换为另一个方向矩阵的最小成本来评估方向相似度。这些模型的限制在元素总和最多为1的方向矩阵中使用。本文提出了一种定性定向相似性计算模型来评估方向相似性,这是基于模糊近距离的模式。新模型忽略了基本方向之间的关系,并在相似性评估中具有广泛的应用。

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