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

[[Category:Publications on intuitionistic fuzzy sets|{{PAGENAME}}]]
[[Category:Publications in Notes on IFS|{{PAGENAME}}]]
[[Category:Publications in 2016 year|{{PAGENAME}}]]
{{issue/title
 | title           =  A method for optimizing a bidding strategy for online advertising through the use of intuitionistic fuzzy systems
 | shortcut        = nifs/22/2/99-107
}}
{{issue/author
 | author          = Quetzali Madera
 | institution     = Institute of Technology, Calzada Tecnologico s/n
 | address         =  Tijuana, Mexico
 | email-before-at = quetzalimadera
 | email-after-at  = tectijuana.edu.mx
}}
{{issue/author
 | author          =  Oscar Castillo
 | institution     = Institute of Technology, Calzada Tecnologico s/n
 | address         =  Tijuana, Mexico
 | email-before-at = ocastillo
 | email-after-at  = tectijuana.mx
}}
{{issue/author
 | author          = Mario García-Valdez
 | institution     = Institute of Technology, Calzada Tecnologico s/n
 | address         =  Tijuana, Mexico
 | email-before-at = 
 | email-after-at  = 
}}
{{issue/author
 | author          = Alejandra Mancilla
 | institution     = Institute of Technology, Calzada Tecnologico s/n
 | address         =  Tijuana, Mexico
 | email-before-at = 
 | email-after-at  = 
}}
{{issue/author
 | author          = Evdokia Sotirova
 | institution     = Intelligent Systems Laboratory, “Prof. Dr. Asen Zlatarov” University
 | address         =  Burgas, Bulgaria
 | email-before-at = esotirova
 | email-after-at  = btu.bg
}}
{{issue/author
 | author          = Sotir Sotirov
 | institution     = Intelligent Systems Laboratory, “Prof. Dr. Asen Zlatarov” University
 | address         =  Burgas, Bulgaria
 | email-before-at = ssotirov
 | email-after-at  = btu.bg
}}
{{issue/data
 | conference      =  International Conference on Intuitionistic Fuzzy Sets Theory and Applications, 20–22 April 2016, Beni Mellal, Morocco
 | issue           = [[Notes on Intuitionistic Fuzzy Sets/22/2|"Notes on IFS", Volume 22, 2016, Number 2]], pages 99—107
 | file            = NIFS-22-2-099-107.pdf
 | format          = PDF
 | size            = 127
 | 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             = 03E72.
 | references      = 
#	Atanassov, K. (1999) Intuitionistic Fuzzy Sets. Springer, Heidelberg.
#	Atanassov, K. (2012) On Intuitionistic Fuzzy Sets Theory, Springer, Berlin.
#	Amjady, N. (2006). Day-ahead price forecasting of electricity markets by a new fuzzy neural network. Power Systems, IEEE Transactions on, 21(2), 887–896.
#	Anbazhagan, S., & Kumarappan, N. (2013). Day-ahead deregulated electricity market price forecasting using recurrent neural network. Systems Journal, IEEE, 7(4), 866–872.
#	Chang, P. C., & Liu, C. H. (2008). A TSK type fuzzy rule based system for stock price prediction. Expert Systems with Applications, 34(1), 135–144.
#	Dao, T. H., Jeong, S. R., & Ahn, H. (2012). A novel recommendation model of location-based advertising: Context-Aware Collaborative Filtering using GA approach. Expert Systems with Applications, 39(3), 3731–3739.
#	Fan, T. K., & Chang, C. H. (2011). Blogger-centric contextual advertising. Expert Systems with Applications, 38(3), 1777–1788. 
#	García-Valdez, M., Trujillo, L., de Vega, F. F., Guervós, J. J. M., & Olague, G. (2013). EvoSpace: a distributed evolutionary platform based on the tuple space model (pp. 499–508). Springer Berlin Heidelberg.
#	García-Valdez, M., Trujillo, L., de Vega, F. F., Guervós, J. J. M., & Olague, G. (2013). Evospace-interactive: A framework to develop distributed collaborative-interactive evolutionary algorithms for artistic design. Machado et al. [MMC13], 121–132.
#	Guerini, M., Strapparava, C., & Stock, O. (2008, May). Valentino: A Tool for Valence Shifting of Natural Language Texts. Proceedings of LREC’2008, 243–246.
#	Keng, C. J., & Liu, C. C. (2013). Can avatar and self-referencing really increase the effects of online 2-D and 3-D advertising?. Computers in Human Behavior, 29(3), 791–802.
#	Morris, Garrett M., et al. (1998) Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. Journal of Computational Chemistry 19.14, 1639–1662.
#	Trillas, E., Bonissone, P. P., Magdalena, L., & Kacprzyk, J. (Eds.). (2012). Combining Experimentation and Theory: A Hommage to Abe Mamdani (Vol. 271). Springer Science & Business Media.
#	Wang, Y. F. (2003). Mining stock price using fuzzy rough set system. Expert Systems with Applications, 24(1), 13–23.
#	Wu, Z., Xu, G., Lu, C., Chen, E., Zhang, Y., & Zhang, H. (2013). Position-wise contextual advertising: Placing relevant ads at appropriate positions of a web page. Neurocomputing, 120, 524–535. 

 | citations       = 
 | see-also        = 
}}