SAGEL: smart address geocoding engine for supply-chain logistics

Abhranil Chatterjee, Janit Anjaria, Sourav Roy, A. Ganguli, K. Seal
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引用次数: 12

Abstract

With the recent explosion of e-commerce industry in India, the problem of address geocoding, that is, transforming textual address descriptions to geographic reference, such as latitude, longitude coordinates, has emerged as a core problem for supply chain management. Some of the major areas that rely on precise and accurate address geocoding are supply chain fulfilment, supply chain analytics and logistics. In this paper, we present some of the challenges faced in practice while building an address geocoding engine as a core capability at Flipkart. We discuss the unique challenges of building a geocoding engine for a rapidly developing country like India, such as, fuzzy region boundaries, dynamic topography and lack of convention in spellings of toponyms, to name a few. We motivate the need for building a reliable and precise address geocoding system from a business perspective and argue why some of the commercially available solutions do not suffice for our requirements. SAGEL has evolved through 3 cycles of solution prototypes and pilot experiments. We describe the learnings from each of these phases and how we incorporated them to get to the first production-ready version. We describe how we store and index map data on a SolrCloud cluster of Apache Solr, an open-source search platform, and the core algorithm for geocoding which works post-retrieval in order to determine the best matches among a set of candidate results. We give a brief description of the system architecture and provide accuracy results of our geocoding engine by measuring deviations of geocoded customer addresses across India, from verified latitude, longitude coordinates of those addresses, for a sizeable address set. We also measure and report our system's ability to geocode up to different region levels, like city, locality or building. We compare our results with those of the geocoding service provided by Google against a set of addresses for which we have verified latitude-longitude coordinates and show that our geocoding engine is almost as accurate as Google's, while having a higher coverage.
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SAGEL:供应链物流的智能地址地理编码引擎
随着近年来印度电子商务行业的爆炸式发展,地址地理编码问题,即将文本地址描述转换为地理参考,如纬度、经度坐标,已经成为供应链管理的核心问题。依赖于精确和准确的地址地理编码的一些主要领域是供应链履行、供应链分析和物流。在本文中,我们提出了在构建地址地理编码引擎作为Flipkart核心功能时在实践中面临的一些挑战。我们讨论了为印度这样一个快速发展的国家构建地理编码引擎所面临的独特挑战,例如,模糊的区域边界、动态地形和缺乏地名拼写的惯例,等等。我们从业务的角度激发了构建可靠和精确的地址地理编码系统的需求,并讨论了为什么一些商业上可用的解决方案不能满足我们的需求。SAGEL经历了3个解决方案原型和试点实验的周期。我们描述了从每个阶段学到的东西,以及我们如何将它们整合到第一个生产就绪版本中。我们描述了如何在Apache Solr(一个开源搜索平台)的SolrCloud集群上存储和索引地图数据,以及地理编码的核心算法,该算法在检索后工作,以便在一组候选结果中确定最佳匹配。我们给出了系统架构的简要描述,并通过测量印度各地地理编码客户地址的偏差,从这些地址的经过验证的经纬度坐标,为相当大的地址集提供了地理编码引擎的准确性结果。我们还测量并报告系统在不同区域级别(如城市、地区或建筑物)进行地理编码的能力。我们将我们的结果与Google提供的地理编码服务的结果进行比较,并对一组我们已经验证了经纬度坐标的地址进行比较,结果表明我们的地理编码引擎几乎和Google的一样准确,同时具有更高的覆盖率。
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