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Entity recognition and disambiguation for natural-language spatial search queries

机译:自然语言空间搜索查询的实体识别和歧义消除

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In our modern world, search engines have been proposed as one of the challenging research areas. One of the main issues in search engines studies is human computer interaction, which its aim is to understand user's needs. If there is no right query processing approach, the results will be invalid in most cases. Therefore, in this paper we present a new approach to process and analyze the queries for spatial search engines. Our algorithm is implemented in the three steps, including: iterative segmentation of the query, sub-queries processing by finding appropriate candidates for the location-names, the location-types and spatial relationships and finally checking the relationships among these candidates in validation phase. Generally using our method has two major advantages as the search engines can provide the capability of spatial analysis based on the specific process which leads to a better interaction between the users and the search application in geospatial realm and secondly because of the disambiguation technique, user reaches the more desirable result.
机译:在我们的现代世界中,已经提出搜索引擎作为具有挑战性的研究领域之一。搜索引擎研究的主要问题之一是人机交互,其目的是了解用户的需求。如果没有正确的查询处理方法,则在大多数情况下结果将无效。因此,在本文中,我们提出了一种新的方法来处理和分析空间搜索引擎的查询。我们的算法在以下三个步骤中实现,包括:查询的迭代分段,通过为位置名称,位置类型和空间关系找到合适的候选者并最终在验证阶段检查这些候选者之间的关系来进行子查询处理。通常,使用我们的方法有两个主要优点,因为搜索引擎可以根据特定过程提供空间分析的能力,从而导致用户与地理空间领域中的搜索应用程序之间更好的交互;其次,由于使用了歧义消除技术,用户可以更理想的结果。

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