| Title | Application of Machine Learning to Identify Counterfeit Website |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Wu, KuanTing, Chou, ShingHua, Chen, ShyhWei, Tsai, ChingTsorng, Yuan, ShyanMing |
| Conference Name | Proceedings of the 20th International Conference on Information Integration and Web-based Applications & Services |
| Publisher | ACM |
| Conference Location | New York, NY, USA |
| ISBN Number | 978-1-4503-6479-9 |
| Keywords | composability, counterfeit website, Decision Tree, fraudulent website, logistic regression, Metrics, pubcrawl, Resiliency, support vector machine, Support vector machines |
| Abstract | 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. |
| URL | http://doi.acm.org/10.1145/3282373.3282407 |
| DOI | 10.1145/3282373.3282407 |
| Citation Key | wu_application_2018 |
Application of Machine Learning to Identify Counterfeit Website