Detecting click fraud in online advertising: a data mining approach

By Richard Jayadi Oentaryo, Ee-Peng Lim, Michael Finegold, David Lo, Feida Zhu, Clifton Phua, Eng Yeow Cheu, Ghim-Eng Yap, Kelvin Sim, Minh Nhut Nguyen and 8 more. 2014

95 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Yang Liu
2. Qiang Yang
3. Tianjian Chen
4. Tao Fan
5. Kewei Cheng
6. Yilun Jin
7. Xiaojun Wan
8. Yu Zhang

In Information Systems

1. Tianjian Chen
2. Qiang Yang
3. Kewei Cheng
4. Yang Liu
5. Weike Pan
6. Michael R. Lyu
7. Steffen Rendle
8. Irwin King

Citations in the corpus

• SecureBoost: A Lossless Federated Learning Framework (2019, methodology): “As one of the most widely-used machine-learning algorithms, the gradient-tree boosting model (Friedman et al. 2000) excels in many machine learning tasks, such as fraud detection (Oentaryo et al. 2014), feature selection (Li et al. 2017) and product recommendation (He et al. 2014).”