基于主题建模的货运供应商推理

Proceedings of the 5th Workshop on Data Science for Macro-modeling with Financial and Economic Datasets Pub Date : 2019-06-30 DOI:10.1145/3336499.3338013

Chi-hung Chen

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引用次数: 0

摘要

本研究将潜在狄利克雷分配应用于美国自动舱单系统的提单数据。我们定义了一个“字袋”，其中每个协调税则号代表一个文件，每个托运人名称是一个标记，装运数量是矩阵的元素。结果表明，该主题模型能够对同一行业的部分托运人进行分类。

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Shipment Supplier Inference Using Topic Modeling

This research applies Latent Dirichlet Allocation on United States Automated Manifest System Bill of Lading data. We define a "bag of word" where each Harmonized tariff code represents a document, each shipper name be a token and count of shipments to be element of matrix. The result shows that topic model is able to classify some shippers of the same industries.

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Proceedings of the 5th Workshop on Data Science for Macro-modeling with Financial and Economic Datasets

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