A new approach to build a geographical taxonomy of adjacency automatically using the latent semantic indexing method

Omar El Midaoui, A. El Qadi, M. D. Rahmani, D. Aboutajdine
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引用次数: 4

Abstract

In this paper, we introduce an approach for constructing a geographical taxonomy of adjacency for a country, to be used in reformulating spatial queries. The proposed approach uses the best-ranked documents retrieved by the search engine while submitting the spatial entity composed of a spatial relationship and a noun of a city A. Then, apply to it the Latent Semantic Indexing method to found the nearest cities Bi to A, and proceed to a step of validation of each link by verifying if A is also found in the results of the cities Bi. In our experiments, we constructed a geographical taxonomy of adjacency for Morocco. We varied the spatial relationship used in the step of documents retrieving to compare the results of the different spatial relationships, and we used google web services as a search engine to compare the results returned in every case. Then we used the constructed taxonomy in geographical query reformulation. We have used the Un-interpolated Average Precision (UAP) to compare the returned documents before and after reformulation. According to our results, we note that reformulating geographical queries based on our built taxonomy improves widely the precision of the queries.
提出了一种利用潜在语义索引自动建立地理邻接分类的新方法
在本文中,我们介绍了一种构建邻接地理分类的方法,用于重新制定空间查询。该方法使用搜索引擎检索到的排名最高的文档,同时提交由空间关系和城市a的名词组成的空间实体。然后,对其应用潜在语义索引方法来找到离a最近的城市Bi,并通过验证在城市Bi的结果中是否也找到a来验证每个链接的步骤。在我们的实验中,我们为摩洛哥建立了一个地理邻接分类。我们改变了文档检索步骤中使用的空间关系,以比较不同空间关系的结果,并且我们使用google web服务作为搜索引擎来比较每种情况下返回的结果。然后将构造好的分类法用于地理查询的重新表述。我们使用了未插值的平均精度(UAP)来比较重新表述前后返回的文档。根据我们的结果,我们注意到基于我们构建的分类法重新制定地理查询大大提高了查询的精度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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