Design and Validation of an Attention Model of Web Page Users

In this paper, we propose a model to predict the locations of the most attended pictorial information on a web page and the attention sequence of the information. We propose to divide the content of a web page into conceptually coherent units or objects, based on a survey of more than 100 web pages. The proposed model takes into account three characteristics of an image object: chromatic contrast, size, and position and computes a numerical value, the attention factor. We can predict from the attention factor values the image objects most likely to draw attention and the sequence in which attention will be drawn. We have carried out empirical studies to both develop and determine the efficacy of the proposed model. The study results revealed a prediction accuracy of about 80% for a set of artificially designed web pages and about 60% for a set of real web pages sampled from the Internet. The performance was found to be better (in terms of prediction accuracy) than the visual saliency model, a popular model to predict human attention on an image