Biblio
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2018. Application of Machine Learning to Identify Counterfeit Website. Proceedings of the 20th International Conference on Information Integration and Web-based Applications & Services. :321–324.
Recent years the prevalence of fraudulent websites has become more severe than before. Fraudulent ecommerce websites that sell counterfeit goods not only cost financial damage to consumers but also have a great impact on Internet industry. Nowadays, there is not an effective way to confront these websites. In this paper, we look forward to achieving three goals: find the characteristics of counterfeit websites, train models for classifying ecommerce websites and provide a service to help consumers distinguish counterfeit websites from legitimate ones.