A method and apparatus for identifying address ownership and distributing logistics tasks

Abstract

A method and apparatus for home identification of address are provided in an embodiment of that present application, the method comprises splitting a receiving address of a logistics task into a plurality of sub-addresses corresponding to different geographical levels, by using a match data set, matching based on that plurality of sub-addresses, determining a target area to which the recipient address belongs in the divided plurality of areas, so that the multi-classifier based on a large number of samples is used to match the address of the receiver. The method can not only solve the problemthat the address adopts abbreviation or nickname to lead to the recognition failure, but also can learn the corresponding weights according to the wrong words and the wrong part of the address of theuser. Compared with the name matching of the campus, the method has more generalization ability and stronger robustness, and improves the accuracy of the home identification of the received address.

Description

technical field [0001] The present application relates to the field of network technology, in particular to a method and device for identifying the attribution of an address, a method and device for distributing logistics tasks, and a logistics system. Background technique [0002] With the rapid development of the e-commerce industry and the logistics industry, the online shopping behavior of college students has surged, and the majority of campus users have become the main force of online shopping. Shipping and other comprehensive logistics services. [0003] Campus post stations often have a large number of packages piled up. In order to alleviate this problem and improve the user experience of campus teachers and students, a campus crowdsourcing service platform emerged as the times require, allowing campus users to pick up a few more packages during their free time and deliver them to other places. In the hands of campus users, it not only fully taps the idle energy of...

AI Technical Summary

Problems solved by technology

[0005] After research, the applicant found that, first of all, GeoHash encoding is divided into rectangular areas according to the range of latitude and longitude, and each rectangular area is encoded, but most of the campus The address fences are all irregular shapes. If the campus is forcibly divided into rectangular blocks, it will inevitably cause inaccurate identification of the surrounding areas of the campus, resulting in the inaccurate identification of some receiving addresses.

Secondly, the text matching of the campus name only uses the information of the campus dimension in the recipient address. If the recipient address is not filled in standardizedly, the campus name in the recipient address is an abbreviation or nickname, which will directly reduce the accuracy of campus text matching.

Based on the above reasons, due to the inability to accurately match the campus for the receiving address, the distribution of logistics tasks cannot be done accurately

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