Mining Online Shopping Frauds—A Non-Data Mining Approach
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IACSIT Press
Cited by 6 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. Vulnerability of Gen-Z to E-Commerce Deception on Consumer's Belief Categories in Online Product Recommendations Systems;Quality Innovation Prosperity;2024-07-31
2. Analyzing Bank Account Information of Nominees and Scammers in Thailand: Insights from ChaladOhn Website Data;2023 International Conference on Digital Applications, Transformation & Economy (ICDATE);2023-07-14
3. “I Have Only Checked after the Event”: Consumer Approaches to Safe Online Shopping;Victims & Offenders;2022-10-03
4. Consumer Fraud in Online Shopping: Detecting Risk Indicators through Data Mining;International Journal of Electronic Commerce;2022-06-24
5. Chaladohn: Website for Avoiding of Online Shopping Scams in Thailand;2022 IEEE 12th Symposium on Computer Applications & Industrial Electronics (ISCAIE);2022-05-21
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