발간년도 : [2022]
| 논문정보 |
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| 논문명(한글) |
[Vol.17, No.2] A Design and Implementation of Differentiated Logistic Data Analytic Platform by Investigating Existing Similar Service Functions |
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| 논문투고자 |
Keejun Han, Hoon Jung, Dong-gil Na |
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| 논문내용 |
Despite the rapid growth of the non-face-to-face economy, customized marketing information and sales strategy provision services for small and medium-sized sellers are insufficient, highlighting the need to design and establish an advanced logistic data analytic platform is essential. Therefore, this study analyzed whether there are areas where existing functions can be improved or new functions can be added using big data and AI functions through analysis of domestic logistic analytic platforms. As a result, it seemed that existing services needed to establish data-sharing strategies and further machine learning solutions to investigate multiple internal and external data sources. In addition, in order to secure differentiation from existing services, a machine learning algorithm was designed to predict the weight and price of targeted items based on bill of landing data. Throughout the experiment, we observed that while LSTM does not work well for overall data, the linear regression and MLP models showed good overall performance. It confirmed the models could be used to provide the weight and price prediction services for countries and items targeted to export. The models built in this study are dockerized as a public API service in the future so that researchers and developers can use them actively. |
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