Abstract
The description of a product or an ad’s text can be rewritten in many ways if other text fragments similar in meaning substitute different words or phrases. A good selection of words or phrases, composing an ad, is very important for the creation of an advertisement text, as the meaning of the text depends on this and it affects in a positive or a negative way the interest of the possible consumers towards the advertised product. In this paper we present a method for the optimization of advertisement texts through the use of interactive evolutionary computing techniques. The EvoSpace platform is used to perform the evolution of a text, resulting in an optimized text, which should have a better impact on its readers in terms of persuasion.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
McQuarrie, Edward F., David, M.: Visual rhetoric in advertising: Text-interpretive, experimental, and reader-response analyses. J. Consum. Res. 26(1), 37–54 (1999)
De Jong, K.A.: Evolutionary computation–a unified approach. MIT Press, Cambridge (2006)
Bäck, T.: Evolutionary Algorithms In Theory And Practice: Evolution Strategies, Evolutionary Programming, Genetic Algorithms, vol. 996. Oxford University Press, Oxford (1996)
Whitley, D.: A genetic algorithm tutorial, Statistics and Computing, p. 65. Kluwer Academic Publishers 4.2, Norwell (1994)
Takagi, H.: Interactive evolutionary computation: fusion of the capabilities of EC optimization and human evaluation. Proc. IEEE 89(9), 1275 (2001)
Malcolm, J.A., Peter L.: An approach to detecting article spinning. In: Proceedings of the Third International Conference on Plagiarism (2008)
García, M., et al.: EvoSpace: a distributed evolutionary platform based on the tuple space model. In: Applications of Evolutionary Computation, pp. 499–508. Springer, Berlin (2013)
Davis, H.: Google Advertising Tools: Cashing in with AdSense, AdWords, and the Google APIs. O’reilly, Cambridge (2006)
Fernández, F., et al.: EvoSpace-interactivo: una herramienta para el arte y diseño interactivo y colaborativo, pp. 220–228. Algoritmos Evolutivos y Bioinspirados, IX Congreso Español de Metaheurísticas (2013)
Chevrolet.: Chevrolet Mexico Ad description (2013). http://www.chevrolet.com.mx/spark-2014.html.Accessed 12 Dec 2013
Hartigan, J.: Clustering Algorithms. Wiley, New York (1975)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this paper
Cite this paper
Madera, Q., Garcia, M., Castillo, O. (2016). Fuzzy Logic for Improving Interactive Evolutionary Computation Techniques for Ad Text Optimization. In: Atanassov, K., et al. Novel Developments in Uncertainty Representation and Processing. Advances in Intelligent Systems and Computing, vol 401. Springer, Cham. https://doi.org/10.1007/978-3-319-26211-6_25
Download citation
DOI: https://doi.org/10.1007/978-3-319-26211-6_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-26210-9
Online ISBN: 978-3-319-26211-6
eBook Packages: Computer ScienceComputer Science (R0)