  People often refer to a place of interest (POI) by an alias. In e-commerce
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.
