Research on Information Technology with Detecting the Fraudulent Clicks Using Classification Method
Ji Hong Yan, Wen Rong Jiang · Advanced materials research · 2013
This paper aims to find an effective solution to detect fraudulent clicks from commissioners’ click logs. Given user’s click information of ads, we want to predict the user’s fraudulent label – malicious or not. Based on training set, we build our classification models for fraudulent click detection. We first create and extract features for the raw log data we show above. Next, we choose models by evaluating classifiers, and then build an ensemble model. Finally, we applied our model on the real dataset for human judge reference.