返回
Inspection-oriented coding service based on machine learning and semantics mining
DOI:10.1016/j.eswa.2006.01.019.png)
摘要
En 中文
HS codes have been adopted by the majority of countries as being the basis for import and export inspection and the generation of trade statistics. Customs authorities and international traders need a HS code query tool to make their processing efficient and automatic. Since HS codes are identified at 5-7 levels of classification, then any intelligent coding service will need to combine a knowledge database, with the techniques of data mining, machine learning and semantics reasoning. In this paper, the authors propose a comprehensive solution for such a coding service. The architecture, related techniques, technical solution and implementation considerations for the proposed system have been provided. Several of the proposed functions and implementation techniques have been developed and deployed by the Shanghai International Airport Entry-Exit Inspection and Quarantine Bureau. The coding service has been published as a Web service, and has the potential to be widely used by authorities and international traders around the world. The proposed system may also be appropriate for other applications that relate to code or classification processes, such as RFID-based or product ontology based applications. (c) 2006 Elsevier Ltd. All rights reserved.
Keyword:
HS codes
semantics mining
knowledge database
web services
AI总结
对已上传原文的论文进行重点信息的提取,主要内容包括:简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.5
论文数:
3.0W
被引数:
11.4W
机构
暂无机构信息
引用论文
没有更多内容

