The task of assigning internationally accepted commodity codes (aka HS codes) to traded goods is a critical function of customs offices. Like court decisions made by judges, this task follows the doctrine of precedent and can be nontrivial even for experienced officers. Together with the Korea Customs Service (KCS), we propose a first-ever explainable decision supporting model that suggests the most likely subheadings (i.e., the first six digits) of the HS code. The model also provides reasoning for its suggestion in the form of a document that is interpretable by customs officers. We evaluated the model using 5,000 cases that recently received a classification request. The results showed that the top-3 suggestions made by our model had an accuracy of 93.9\% when classifying 925 challenging subheadings. A user study with 32 customs experts further confirmed that our algorithmic suggestions accompanied by explainable reasonings, can substantially reduce the time and effort taken by customs officers for classification reviews.

翻译：为贸易商品分配国际公认的HS编码（即商品统一分类编码）是海关的关键职能。如同法官作出的法庭判决，这项任务遵循判例原则，即便对经验丰富的官员而言也颇具难度。我们与韩国海关（KCS）合作，首次提出一种可解释的决策支持模型，能够推荐最可能的HS编码子目（即前六位数字）。该模型还能以海关官员可解读的文档形式提供其建议的依据。我们利用近期收到分类请求的5000个案例对模型进行了评估。结果表明，在对925个具有挑战性的子目进行分类时，模型前三建议的准确率达93.9%。一项针对32名海关专家的用户研究进一步证实，我们的算法建议附有可解释的推理过程，能显著减少海关官员进行分类审查所需的时间与精力。