Abstract
Due to the introduction of the cloud platform, the business data of rail-water combined transport is concentrated and deposited in the cloud, which makes the secondary utilization of the big data of combined transport possible. At the same time, with the rapid growth of orders, the demand for intelligent matching arises at the historic moment. Based on the big data support system of rail-water combined transportation cloud platform, this paper constructs a hierarchical recommendation model for the application of order matching big data. Combined with distributed data computing technology, the personalized matching algorithm is studied, and the performance test of the algorithm is carried out. IAMS is used to deploy the distributed recommendation system based on different algorithms, and acceptance and coverage tests are carried out to verify the effectiveness of IOMS matching algorithm. It is of great practical value to optimize the matching efficiency of orders and thus improve the service quality and business handling efficiency of the freight e-commerce platform.
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Acknowledgements
This research was also funded by Sichuan Agricultural University education reform project X2013039, X2014025 “Agricultural Information Engineering” Sichuan key laboratory of higher education.
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Huang, Q., Chen, D., Pan, J., Yuan, J., Wang, M., Ni, S. (2021). Research on Order Matching Based on the Big Data of Rail-Water Combined Transportation. In: Balas, V.E., Pan, JS., Wu, TY. (eds) Advances in Smart Vehicular Technology, Transportation, Communication and Applications. Smart Innovation, Systems and Technologies, vol 226. Springer, Singapore. https://doi.org/10.1007/978-981-16-1209-1_23
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DOI: https://doi.org/10.1007/978-981-16-1209-1_23
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