Paper Info
Title
Modeling browsing behavior for click analysis in sponsored search
Abstract
Clickthrough rate provides a fundamental measure of advertising quality, which is widely used in ad selection strategies. However, ads placed in contexts where they are rarely viewed, or where users are unlikely to be interested in commercial results, may receive few clicks regardless of their quality. In this paper, we gain insight into user browsing and click behavior for the purpose of click analysis in sponsored search domain. The list of ads displayed on a page, the user's initial motivation to browse this list, and the persistence of the user are among the contextual factors considered in this paper. We propose a probabilistic model for user's browsing and click behavior using these contextual factors. To evaluate the performance of the model, we compare it with state-of-the-art methods. The experimental results confirm that these contextual factors can better reflect user browsing and click behavior in sponsored search.
Year
DOI
Venue
2012
10.1145/2396761.2398563
CIKM
Keywords
Field
DocType
advertising quality,probabilistic model,user browsing,ad selection strategy,search domain,click analysis,clickthrough rate,contextual factor,commercial result,browsing behavior,bayesian inference
Data mining,World Wide Web,Bayesian inference,Information retrieval,Computer science,Click path,Statistical model,Click model
Conference
Citations 
PageRank 
References 
5
0.43
15
Authors
2
Name
Order
Citations
PageRank
Azin Ashkan162629.68
Charles L.A. Clarke23289286.78