Predicting the probability that a user will click on a specific advertisement has been a
prevalent issue in online advertising, attracting much research attention in the past decades …

As a prevalent problem in online advertising, CTR prediction has attracted plentiful attention
from both academia and industry. Recent studies have been reported to establish CTR …

Click Fraud is a fraudulent act of clicking on pay-per-click advertisements to increase the
site's revenue or to drain revenue from the advertiser. This illegal act has been putting …

The ability to anticipate whether a user will click on an item is one of the most crucial aspects
of operating an e-commerce business, and clickthrough rate prediction is an attempt to …

The construction of a financial risk prediction model has become the need of the hour due to
long-term and short-term violations in the financial market. To reduce the default risk of peer …

Credit scoring models have been widely used in traditional financial institutions for many
years. Using these models in P2P Lending have limitations. First, the credit data of P2P …

Feature selection has emerged as a craft, using which we boost the performance of our
learning model. Feature or Attribute Selection is a data preprocessing technique, where only …

Click fraud is a fast-growing cyber-criminal activity with the aim of deceptively clicking on the
advertisements to make the profit to the publisher or cause loss to the advertiser. Due to the …

Gradient boosting decision tree (GBDT) is a mainstream model for advertisement click-
through rate (CTR) prediction. Since the complex working mechanism of GBDT, advertising …

Click fraud is the sort of deception in which traffic figures for online ads are intentionally
inflated. For businesses that advertise online, click fraud may occur often, resulting in …