Spatial search strategies for open government data: a systematic comparison

Auriol Degbelo, Brhane Bahrishum Teka
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引用次数: 11

Abstract

The increasing availability of open government datasets on the Web calls for ways to enable their efficient access and searching. There is however an overall lack of understanding regarding spatial search strategies which would perform best in this context. To address this gap, this work has assessed the impact of different spatial search strategies on performance and user relevance judgment. We harvested machine-readable spatial datasets and their metadata from three English-based open government data portals, performed metadata enhancement, developed a prototype and performed both a theoretical and user-based evaluation. The results highlight that (i) switching between area of overlap and Hausdorff distance for spatial similarity computation does not have any substantial impact on performance; and (ii) the use of Hausdorff distance induces slightly better user relevance ratings than the use of area of overlap. The data collected and the insights gleaned may serve as a baseline against which future work can compare.
开放政府数据的空间搜索策略:系统比较
网络上开放政府数据集的可用性越来越高,这就要求有办法使它们能够有效地访问和搜索。然而,对于在这种情况下表现最好的空间搜索策略,总体上缺乏理解。为了解决这一差距,本研究评估了不同空间搜索策略对性能和用户相关性判断的影响。我们从三个基于英语的开放政府数据门户获取机器可读的空间数据集及其元数据,进行元数据增强,开发原型并进行理论和基于用户的评估。结果表明:(1)空间相似性计算在重叠面积和Hausdorff距离之间切换对性能没有实质性影响;(ii)使用豪斯多夫距离比使用重叠面积诱导出稍好的用户相关性评级。收集到的数据和见解可以作为未来工作的基准进行比较。
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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