%A Zixuan Zhang,Hao Wang,Liping Zhu,Sanhong eng %T Identifying Risks of HS Codes by China Customs %0 Journal Article %D 2019 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.2096-3467.2018.0506 %P 72-84 %V 3 %N 1 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_4605.shtml} %8 2019-01-25 %X

[Objective] This study tries to utilize patterns from the HS codes to provide effective knowledge service for the China customs taxation. [Methods] We proposed two machine learning-based automatic classification schemes. The first one directly used original HS codes as risk identifiers while the other one relied on the correctness of the HS codes. We also built a SVM prediction model and examined the two schemes from the perspectives of target structures and features, as well as the text length. [Results] We found that the second model required less training efforts and processing time and then reached better accuracy. [Limitations] Only used four-month-data to train the new models. [Conclusions] This study finds an effective way to forecast customs risks, and indicate directions of applicable products.