Title :
Web User Click Intention Prediction by Using Pupil Dilation Analysis
Author :
Joaquin Jadue;Gino Slanzi;Luis Salas; Vel?squez
Author_Institution :
Dept. of Ind. Eng., Univ. of Chile, Santiago, Chile
Abstract :
We propose a novel approach for predicting Web user click intention, using pupil dilation data generated by an eye-tracking device as input. Our goal is to determine if this variable is useful to differentiate choice and no-choice states, and if so, to generate a classification model for predicting choice understood as a click. For this, we performed an experiment with 25 healthy subjects in which gaze position and pupil size was recorded while users choose between several elements on a simulated Web site. Our results show that there is a statistical difference between pupil sizes of chosen elements compared with no chosen ones. Furthermore, we generated a click-intention prediction model, based on Artificial Neural Networks, which obtained an 82% accuracy. These results suggest that this variable could be used from a Web Intelligence point of view as a proxy of Web user behaviour, in order to generate an online recommender to improve Web site structure and content.
Keywords :
"Web sites","Predictive models","Brain modeling","Data models","Logistics","Companies","Visualization"
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2015 IEEE / WIC / ACM International Conference on
DOI :
10.1109/WI-IAT.2015.221