What is it about?
Some places have alias names. I.e. the New York city has an alias "Big Apple". We propose a automatic technique to discover these aliases by using the users' GPS data and delivery addresses on e-commerce platforms. The technique is inspired by our observation that no matter how users describe their delivery address (standard name or alias), the users that refer to the same real-world place in their addresses share similar mobility. So we propose a deep learning based method to capture such "mobility similarity", which is validated to be accurate in discovering the aliases.
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Why is it important?
For the same place, while some refer to it by a standard name, others use its alias. By collecting the aliases of the places are known, we can better understand which place the user is referring to in scenarios like delivery logistics
Perspectives
Hope this research can help the e-commerce, logistics, and web-mapping products to improve their address-related features, so that the users get a better experience, the delivery couriers are not troubled by the alias address problem, and the automation of logistics can be contributed!
Tianfu He
Read the Original
This page is a summary of: POI Alias Discovery in Delivery Addresses using User Locations, November 2021, ACM (Association for Computing Machinery),
DOI: 10.1145/3474717.3483950.
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