POI Alias Discovery in Delivery Addresses using User Locations

Tianfu He, Guochun Chen, Chuishi Meng, Huajun He, Zheyi Pan, Yexin Li, Sijie Ruan, Huimin Ren, Ye Yuan, Ruiyuan Li, Junbo Zhang, Jie Bao, Hui He*, Yu Zheng

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

5 引用 (Scopus)

摘要

People often refer to a place of interest (POI) by an alias. In ecommerce scenarios, the POI alias problem affects the quality of the delivery address of online orders, bringing substantial challenges to intelligent logistics systems and market decision-making. Labeling the aliases of POIs involves heavy human labor, which is inefficient and expensive. Inspired by the observation that the users' GPS locations are highly related to their delivery address, we propose a ubiquitous alias discovery framework. Firstly, for each POI name in delivery addresses, the location data of its associated users, namely Mobility Profile are extracted. Then, we identify the alias relationship by modeling the similarity of mobility profiles. Comprehensive experiments on the large-scale location data and delivery address data from JD logistics validate the effectiveness.

源语言英语
主期刊名29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2021
编辑Xiaofeng Meng, Fusheng Wang, Chang-Tien Lu, Yan Huang, Shashi Shekhar, Xing Xie
出版商Association for Computing Machinery
225-228
页数4
ISBN(电子版)9781450386647
DOI
出版状态已出版 - 2 11月 2021
已对外发布
活动29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2021 - Virtual, Online, 中国
期限: 2 11月 20215 11月 2021

出版系列

姓名GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

会议

会议29th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL 2021
国家/地区中国
Virtual, Online
时期2/11/215/11/21

指纹

探究 'POI Alias Discovery in Delivery Addresses using User Locations' 的科研主题。它们共同构成独一无二的指纹。

引用此