测绘通报 ›› 2024, Vol. 0 ›› Issue (7): 158-163.doi: 10.13474/j.cnki.11-2246.2024.0728

• 技术交流 • 上一篇    下一篇

基于复合特征规则库的多源POI融合方法

王庆社1,2, 杨川石1,2, 郭思慧1,2   

  1. 1. 北京市测绘设计研究院, 北京 100045;
    2. 城市空间信息工程北京市重点实验室, 北京 100045
  • 收稿日期:2024-01-19 发布日期:2024-08-02
  • 通讯作者: 郭思慧。E-mail:guosihui@bism.cn
  • 作者简介:王庆社(1973—),男,硕士,高级工程师,主要从事地图数据库建设与电子地图研究。E-mail:zhw20031108@126.com

Multi-source POI fusion method based on composite feature rule library

WANG Qingshe1,2, YANG Chuanshi1,2, GUO Sihui1,2   

  1. 1. Beijing Institute of Surveying and Mapping, Beijing 100045, China;
    2. Beijing Key Laboratory of Urban Spatial Information Engineering, Beijing 100045, China
  • Received:2024-01-19 Published:2024-08-02

摘要: 多源POI融合是指将不同来源的POI数据集成为一个统一、准确且全面的数据库。POI数据作为国家地理信息公共服务平台(天地图)的重要数据资源之一,如何有效融合其他多种POI数据源,使天地图POI数据现势性、准确性及丰富性不断提高,是天地图建设的关键技术之一。当前有关POI数据融合方法的研究在测绘、地理信息系统及大数据和人工智能领域都受到了广泛关注,并取得了一定进展。但由于POI文本类属性的复杂性与多样性,在实际工程应用时如何有效判断POI的属性相似度仍面临挑战。针对天地图POI数据快速更新的迫切需要,以及当前多源POI数据融合方法存在的不足,本文提出一种基于复合特征规则库的多源POI融合方法,为天地图的数据更新与母库建设提供技术支撑。

关键词: POI, 空间数据融合, 复合特征规则库, 天地图, 地理信息系统

Abstract: Multi-source POI fusion refers to integrating POI datasets from different sources into a unified, accurate, and comprehensive database. POI data, as one of the crucial data resources for the National Geographic Information Public Service Platform (Tianditu), poses a key technological challenge in the construction of Tianditu—namely, how to effectively merge various POI data sources to continuously enhance the timeliness, accuracy, and richness of Tianditu's POI data. Research on methods for POI data fusion has garnered widespread attention in the fields of surveying and mapping, geographic information systems, as well as big data and artificial intelligence. Substantial progress has been made in this regard. However, due to the complexity and diversity of POI textual attributes, effectively determining the similarity of POI attributes remains a challenge in practical engineering applications. Given the urgent need for rapid updates to Tianditu's POI data and the shortcomings of current multiple-source POI data fusion methods, this paper proposes a multi-source POI fusion method based on a composite feature rule library. This method aims to provide technical support for the data updates and master database construction of Tianditu.

Key words: POI data, spatial data fusion, composite feature rule library, Tianditu, GIS

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