Optimizing Web Content Presentation: A Online PSO Approach

Authors:
Alfredo Milani;Valentino Santucci;Clement Leung
Affiliations:
Department of Mathematics and Computer Science, University of Perugia, Perugia, Italy;Department of Mathematics and Computer Science, University of Perugia, Perugia, Italy;Department of Computer Science, Hong Kong Baptist University, Hong Kong
Venue:
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Year:
2009

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Abstract

In this paper we propose an approach to optimization of web marketing content based on online discrete particle swarm optimization (PSO) model. The idea behind online PSO is to evaluate the collective user feedback as the PSO objective function which drive particles velocities in the hybrid continuous-discrete space of web content features. The PSO coordinate the process of sampling collective user behavior in order to optimize the web marketing metric. Experiments in the online banner optimization scenario show that the method converges faster than other methods and avoid some common drawbacks such as local optimal and hybrid discrete/continuous features management. The proposed online optimization method is general and can be applied to other web marketing or business intelligent contexts.