P-ISSN 1834-6707
E-ISSN 1834-6715
Vol. 13, Issue 2, 2019September 30, 2019 AEST
Data Mining in Customs Risk Detection With Cost-Sensitive Classification
Data Mining in Customs Risk Detection With Cost-Sensitive Classification
Articles in Vol. 13, Issue 2, 2019
Vol. 13, Issue 2, 2019
- EditorialDavid Widdowson
- The Impact and Countermeasures of New Tax Policy for Cross-Border E-Commerce in ChinaBowen ShiXiang GaoLiangting JiaXiangnan Guo
- Data Analysis Techniques for Enhancing the Performance of CustomsDanilo Desiderio
- Understanding Tax and Customs Policies for Retail Import Cross-Border E-Commerce in ChinaXiangyang Li
- Establishing Risk and Targeting Profiles Using Dara Mining: Decision TreesBassem Chermiti
- Identifying Trade Mis-Invoicing Through Customs Data AnalysisYeon Soo Choi
- Revenue Maximisation Versus Trade Facilitation: The Contribution of Automated Risk ManagementChristopher Grigoriou
- Mirror Analysis as a Support for Risk Management and Valuation: A Practical StudyChristopher Grigoriou
- How Helpful Are Mirror Statistics for Customs Reform? Lessons From a Decade of Operational UseChristopher GrigoriouFrank KalizinjeGael Raballand
- Data Mining in Customs Risk Detection With Cost-Sensitive ClassificationXin Zhou
- PICARD Conference 2020PICARD Conference
Zhou, X. (2019). Data Mining in Customs Risk Detection With Cost-Sensitive Classification. World Customs Journal, 13(2), 115–130. https://doi.org/10.55596/001c.116219