A Bayesian Network Model for Optimizing Advertisements Allocation in Intermediate Online Targeted Advertising

Author

Li, Kai ; Yan, Jianyuan ; Wang, Xiaowen

Author_Institution

Bus. Sch., Nankai Univ., Tianjin

fYear

2008

fDate

12-14 Oct. 2008

Firstpage

1

Lastpage

4

Abstract

Intermediate online targeted advertising (IOTA) is a new business model for online targeted advertising. Posting the right banner advertisement to the right web user at the right time is what advertisements allocation does in IOTA business model. This research uses probability theory to build a theoretical model based on Bayesian network to optimize advertisements allocation. The Bayesian network model allows us to calculate the probability that Web user will click the banner based on historical data. And these can help us to make optimal decision in advertisements allocation. Data availability is also be discussed in this paper. An experiment base on practical data is run to verify the feasibility of the Bayesian network model.

Keywords

advertising; belief networks; Bayesian network model; Web user; banner advertisements; data availability; intermediate online targeted advertising; optimizing advertisements allocation; Advertising; Bayesian methods; Consumer electronics; Costs; Data mining; Electronic commerce; Electronics industry; Probability; Statistics; Web pages;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless Communications, Networking and Mobile Computing, 2008. WiCOM '08. 4th International Conference on

Conference_Location

Dalian

Print_ISBN

978-1-4244-2107-7

Electronic_ISBN

978-1-4244-2108-4

Type

conf

DOI

10.1109/WiCom.2008.2208

Filename

4680397