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http://dx.doi.org/10.9708/jksci.2022.27.08.151

Route matching delivery recommendation system using text similarity  

Song, Jeongeun (Graduate School of information, Yonsei University)
Song, Yoon-Ah (Graduate School of information, Yonsei University)
Publication Information
Journal of the Korea Society of Computer and Information / v.27, no.8, 2022 , pp. 151-160 More about this Journal
Abstract
In this paper, we propose an algorithm that enables near-field delivery at a faster and lowest cost to meet the growing demand for delivery services. The algorithm proposed in this study involves subway passengers (shipper) in logistics movement as delivery sources. At this time, the passenger may select a delivery logistics matching subway route. And from the perspective of the service user, it is possible to select a delivery man whose route matches. At this time, the delivery source recommendation is carried out in a text similarity measurement method that combines TF-IDF&N-gram and BERT. Therefore, unlike the existing delivery system, two-way selection is supported in a man-to-man method between consumers and delivery man. Both cost minimization and delivery period reduction can be guaranteed in that passengers on board are involved in logistics movement. In addition, since special skills are not required in terms of transportation, it is also meaningful in that it can provide opportunities for economic participation to workers whose job positions have been reduced.
Keywords
route recommendation; route matching; text similarity; short-distance delivery; subway delivery; platform service;
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