Optimizing number of online ad impressions per user

Davorin Strehar (2014) Optimizing number of online ad impressions per user. EngD thesis.

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Abstract

This thesis deals with the optimization of displaying online ads (frequency capping), where ad serving represents a cost, and clicks on the ads represent advertising revenue. In this case we would like to display the ad to the user so many times to have the biggest probability of the ad click. For this purpose, we converted the ad serving data to the appropriate format, analyzed it and used machine learning methods to make predictive models with the aim of predicting the optimal number of viewable impressions per user on a specific ad campaign. Afterwards, we used these predictive models in the ad serving simulation where we measured the performance of each procedure. The result of the thesis is the selection of the best procedure to assess the optimal number of viewable ad impressions per user.

Item Type:

Thesis (EngD thesis)

Keywords:

online advertising, prediction, ads, machine learning

Number of Pages:

Language of Content:

Slovenian

Mentor / Comentors:

Name and Surname	ID	Function
izr. prof. dr. Zoran Bosnić	3826	Mentor

Link to COBISS:

http://www.cobiss.si/scripts/cobiss?command=search&base=50070&select=(ID=10540884)

Institution:

University of Ljubljana

Department:

Faculty of Computer and Information Science

Item ID:

2460

Date Deposited:

28 Mar 2014 16:12

Last Modified:

18 Apr 2014 12:10

URI:

http://eprints.fri.uni-lj.si/id/eprint/2460

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