QARTA: An ML-based System for Accurate Map Services
QARTA: An ML-based System for Accurate Map Services
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DOI：
10.14778/3476249.3476279
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发表时间：
2021-07
期刊：
影响因子：
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通讯作者：
Mashaal Musleh;Sofiane Abbar;R. Stanojevic;M. Mokbel
中科院分区：
文献类型：
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作者：
Mashaal Musleh;Sofiane Abbar;R. Stanojevic;M. Mokbel
地图服务在广泛使用的应用中无处不在，包括导航系统、乘车共享和物品/食品递送。尽管有很多努力通过设计更高效的算法来支持这些服务，但我们相信效率不再是这些服务的瓶颈。相反，它是基础道路网络和查询结果的准确性。本文介绍了QARTA;一个开源的成熟的系统，高度准确和可扩展的地图服务。QARTA采用机器学习技术来构建自己的高度准确的地图，不仅在地图拓扑方面，更重要的是在边权重方面。QARTA还采用机器学习技术，根据上下文信息（包括交通方式、位置和一天/一周的时间）来校准其查询答案。QARTA目前部署在卡塔尔国所有出租车和第三大食品配送公司，取代了正在使用的商业地图服务，并实时响应每天数十万个API调用。QARTA的实验评估表明，其可比或更高的准确性比商业服务。
Maps services are ubiquitous in widely used applications including navigation systems, ride sharing, and items/food delivery. Though there are plenty of efforts to support such services through designing more efficient algorithms, we believe that efficiency is no longer a bottleneck to these services. Instead, it is the accuracy of the underlying road network and query result. This paper presents QARTA; an open-source full-fledged system for highly accurate and scalable map services. QARTA employs machine learning techniques to construct its own highly accurate map, not only in terms of map topology but more importantly, in terms of edge weights. QARTA also employs machine learning techniques to calibrate its query answers based on contextual information, including transportation modality, location, and time of day/week. QARTA is currently deployed in all Taxis and the third largest food delivery company in the State of Qatar, replacing the commercial map service that was in use, and responding in real-time to hundreds of thousands of daily API calls. Experimental evaluation of QARTA shows its comparable or higher accuracy than commercial services.