A machine learning approach for detecting customs fraud through unstructured data analysis in social media-Reference-Cited by-同舟云学术

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A machine learning approach for detecting customs fraud through unstructured data analysis in social media

Published:2024-03 Issue: Volume:10 Page:100408
ISSN:2772-6622
Container-title:Decision Analytics Journal
language:en
Short-container-title:Decision Analytics Journal

Author:

Dangsawang Bundidth^ORCID,Nuchitprasitchai Siranee

Publisher

Elsevier BV

Reference49 articles.

1. Understanding intercultural communication:The working principles;McDaniel;Intercult. Commun. Read.,2009

2. Customs [Internet]. Bangkok: Customs Ministry of Finance; 2563 [Adjust 1 2020 ; access when 1 March 2020] accessible from https://www.customs.go.th.

3. Automated detection of smuggled high-risk security threats using deep learning;Jaccard,2016

4. Automated comparison of X-ray images for cargo scanning;Visser,2016

5. Extracting product features for opinion mining using public conversations in Twitter;Othman;Procedia Comput. Sci.,2017

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. To secure an e‐commerce system using epidemic mathematical modeling with neural network;Concurrency and Computation: Practice and Experience;2024-08-29

2. Novel Methodology of Adaptive Machine Learning and Deep Learning System for Detecting the Fraudulent Activities in Financial Sector;2024 IEEE International Conference on Contemporary Computing and Communications (InC4);2024-03-15

3. Efficiency and Protection in International Trade: Real-Time Risk Assessment in the Brazilian Customs Clearance Process;2024

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