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Issue:A method for optimizing a bidding strategy for online advertising through the use of intuitionistic fuzzy systems

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Title of paper: A method for optimizing a bidding strategy for online advertising through the use of intuitionistic fuzzy systems
Author(s):
Quetzali Madera
Institute of Technology, Calzada Tecnologico s/n, Tijuana, Mexico
quetzalimadera@tectijuana.edu.mx
Oscar Castillo
Institute of Technology, Calzada Tecnologico s/n, Tijuana, Mexico
ocastillo@tectijuana.mx
Mario García-Valdez
Institute of Technology, Calzada Tecnologico s/n, Tijuana, Mexico
Alejandra Mancilla
Institute of Technology, Calzada Tecnologico s/n, Tijuana, Mexico
Evdokia Sotirova
Intelligent Systems Laboratory, “Prof. Dr. Asen Zlatarov” University, Burgas, Bulgaria
esotirova@btu.bg
Sotir Sotirov
Intelligent Systems Laboratory, “Prof. Dr. Asen Zlatarov” University, Burgas, Bulgaria
ssotirov@btu.bg
Presented at: International Conference on Intuitionistic Fuzzy Sets Theory and Applications, 20–22 April 2016, Beni Mellal, Morocco
Published in: "Notes on Intuitionistic Fuzzy Sets", Volume 22, 2016, Number 2, pages 99—107
Download:  PDF (127  Kb, File info)
Abstract: Even with the raising popularity of video, audio, and animation content in the Web, the text keeps playing an important role, as well as Web textual ads. Tools for advertising campaigns, such as Google AdWords based on a betting system increase its popularity, but these systems can rapidly consume the user’s money. This paper presents a method for optimizing the bids on the betting system through the use of fuzzy logic techniques. In order to lower the cost of the advertising campaign a fuzzy system is implemented on a Google AdWords advertising campaign. A fuzzy inference system is used to control the maximum bidding price of an advertising campaign, by using as inputs the click-through rate and the current maximum bidding price. Another estimation based of the number of the clicks on one of the advertisement is proposed. The estimation used Intuitionistic Fuzzy Set (IFS).
Keywords: Interactive evolutionary computation, Fuzzy logic, Genetic algorithm, Advertise¬ment text optimization, Intuitionistic fuzzy set.
AMS Classification: 03E72.
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