Title:	TIME AND SPACE CONTEXTUAL INFORMATION IMPROVES CLICK QUALITY ESTIMATION
Author(s):	Mehmed Kantardzic , Brent Wenerstrom , Chamila Walgampaya , Oleksandr Lozitskiy , Sean Higgins , Darren King
ISBN:	978-972-8924-89-8
Editors:	Sandeep Krishnamurthy
Year:	2009
Edition:	Single
Keywords:	Click Fraud, Click Fraud Prevention, Click Traffic Quality, Web Analytics
Type:	Full Paper
First Page:	123
Last Page:	130
Language:	English
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Full Contents:	click to dowload
Paper Abstract:	Click fraud is a type of internet crime that occurs in pay per click online advertising when a person, automated script, or computer program imitates a legitimate user clicking on an ad, for the purpose of generating a charge per click without having actual interest in the ad’s content. We propose Collaborative Click Fraud Detection and Prevention system (CCFDP) V1.0, which integrates client and server side data to score the quality of incoming clicks. In this paper we detail the outlier detection module which describes clicks in terms of space and time context. This module compares past data with the current context as a preprocessing step. Our system will then combine the additional time and space characteristics with the characteristics of a click to score the quality of incoming clicks. We believe that no other commercial or research system for click fraud detection analyze comprehensively time and space context of each click for better estimation of click traffic quality. Some commercial solutions give only partial solutions expressed through their rules and triggers. We found 34.6% of clicks in an application to real data had outlying attribute-values in time and space.
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