Detecting click fraud in online advertising: A data mining approach

• Main Authors: OENTARYO, Richard, LIM, Ee Peng, FINEGOLD, Michael, LO, David, ZHU, Feida, PHUA, Clifton, CHEU, Eng-Yeow, YAP, Ghim-Eng, SIM, Kelvin, PERERA, Kasun, NEUPANE, Bijay, FAISAL, Mustafa, AUNG, Zeyar, WOON, Wei Lee, CHEN, Wei, PATEL, Dhaval, BERRAR, Daniel
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2014
• Subjects: Data mining; Ensemble learning; Feature engineering; Fraud detection; Imbalanced classification; Advertising and Promotion Management; Databases and Information Systems; Information Security; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/1990; https://ink.library.smu.edu.sg/context/sis_research/article/2989/viewcontent/Detecting_Click_Fraud_in_Online_Advertising__A_Data_Mining_Approah2014.pdf
• Institution: Singapore Management University

Click fraud - the deliberate clicking on advertisements with no real interest on the product or service offered - is one of the most daunting problems in online advertising. Building an elective fraud detection method is thus pivotal for online advertising businesses. We organized a Fraud Detection...