An EM Algorithm for Click Fraud Detection

16 Pages Posted: 9 Dec 2015

See all articles by Xuening Zhu

Xuening Zhu

Peking University

Da Huang

Fudan University

Rui Pan

Peking University

Hansheng Wang

Peking University - Guanghua School of Management

Date Written: November 26, 2015

Abstract

This paper is concerned with the problem of click fraud detection. We assume each visitor of a website carries a latent indicator, which labels him/her as a regular or malicious user. Information such as number of clicks, number of page views (PVs) and time difference between consecutive clicks are cooperated in our newly proposed statistical model. We allow those random variables to share the same distribution but with different parameters according to the visitor's type. An EM algorithm is then suggested to obtain the maximum likelihood estimator. As a result, click fraud detection can be implemented by estimating the posterior malicious probability of each visitor. Simulation studies are conducted to assess the finite sample performance. We also demonstrate the usefulness of the proposed method via an empirical analysis of a real life example on search engine marketing.

Keywords: Click Fraud Detection; EM Algorithm; Maximum Likelihood Estimator; Search Engine Marketing

JEL Classification: C3

Suggested Citation

Zhu, Xuening and Huang, Da and Pan, Rui and Wang, Hansheng, An EM Algorithm for Click Fraud Detection (November 26, 2015). Available at SSRN: https://ssrn.com/abstract=2695953 or http://dx.doi.org/10.2139/ssrn.2695953

Xuening Zhu

Peking University ( email )

No. 38 Xueyuan Road
Haidian District
Beijing, Beijing 100871
China

Da Huang

Fudan University ( email )

Beijing West District Baiyun Load 10th
Shanghai, 100045
China

Rui Pan

Peking University ( email )

No. 38 Xueyuan Road
Haidian District
Beijing, Beijing 100871
China

Hansheng Wang (Contact Author)

Peking University - Guanghua School of Management ( email )

Peking University
Beijing, Beijing 100871
China

HOME PAGE: http://hansheng.gsm.pku.edu.cn

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