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Comprehensive survey of similarity measures for ranked based location fingerprinting algorithm

机译:基于排名定位识别算法的相似性措施综合调查

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Ranked Based Fingerprinting uses only ordering indices instead of actual Wi-Fi RSS values in order to make the algorithm insensitive to devices. A key component of the RBF algorithm is a similarity measure which is used to compare and find the closest ranked fingerprints. Previous papers study a few similarity measures; here we study 49 similarity measures in a test with a benchmark with publicly available indoor positioning database. For different similarity measures the positioning accuracy varies from 15.80 m to 55.22 m. The top 3 similarity measures are Lorentzian, Hamming and Jaccard. Hamming and Jaccard similarity measures have been studied in other papers while Lorenzian had not been studied with that kind of problems.
机译:基于排序的指纹使用仅使用排序指数而不是实际的Wi-Fi RSS值,以使算法对设备不敏感。 RBF算法的一个关键组件是用于比较和找到最近排名的指纹的相似度测量。之前的论文研究了一些相似措施;在这里,我们研究了具有公开可用室内定位数据库的基准测试中的49个相似度措施。对于不同的相似性测量,定位精度从15.80米到55.22米之间变化。前3名相似措施是Lorentzian,汉明和Jaccard。在其他论文中已经研究了汉明和Jaccard相似度措施,而Lorenzian未被那种问题与那种问题一起研究过。

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