用于局部搜索的位置的微分概念

Vlad Tanasescu, J. Domingue
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引用次数: 8

摘要

为了提取特定地理实体的特征,特别是一个地方,我们建议使用动态极限标记系统与静态KR模型的经典方法相结合,如本体、词典和地名词典。事实上,我们认为,在本地搜索中,所查询的内容隐含地与地点有关。然而,现有的知识表示(KR)模型,如基于逻辑理论、概念空间、功能或其他的本体论,不能孤立地捕捉一个地方意义的所有方面。因此,我们建议基于潜在的差异概念使用它们的组合,在不承诺任何KR模型的情况下,将意义元素联系起来。稍后可以根据给定任务的需求对不同KR模型的元素进行映射,由支持该任务的元素的KR表示来支持。我们通过将该方法应用于定义为支持同质功能场的位置的地方的概念,即允许我做特定事情的空间区域,同时允许运动的同质性,这意味着之前的场不被任何边界打断,从而展示了该方法在局部搜索中的实用性。
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A differential notion of place for local search
For extracting the characteristics a specific geographic entity, and notably a place, we propose to use dynamic Extreme Tagging Systems in combination with the classic approach of static KR models like ontologies, thesauri and gazetteers. Indeed, we argue that in local search, the what that is queried is implicitly about places. However existing knowledge representation (KR) models, such as ontologies based on logical theories, conceptual spaces, affordance or other, cannot capture in isolation all aspects of the meaning of a place. Therefore we propose to use a combination of them based on the underlying notion of differences, linked elements of meaning without commitment to any KR model. Mapping to elements of different KR models can be made later to follow the requirements of a given task, supported by a KR representation of the elements that support this task. We show the usefulness of the approach for local search by applying it to the notion of place defined as a location that supports a homogeneous affordance field, i.e. the spatial area which allows me the do a particular thing, while allowing the homogeneity of movement, meaning that the previous field is not interrupted by any boundaries.
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