Abstract

We describe the development of a computational cognitive model that explains navigation behavior on the World Wide Web. The model, called SNIF-ACT (Scent-based Navigation and Information Foraging in the ACT cognitive architecture), is motivated by Information Foraging Theory (IFT), which quantifies the perceived relevance of a Web link to a user’s goal by a spreading activation mechanism. The model assumes that users evaluate links on a Web page sequentially and decide to click on a link or to go back to the previous page by a Bayesian satisficing model (BSM) that adaptively evaluates and selects actions based on a combination of previous and current assessments of the relevance of link texts to information goals. SNIF-ACT 1.0 utilizes the measure of utility, called information Wai-Tat Fu is an applied cognitive scientist with interests in human–computer interaction, cognitive modeling, information seeking, interactive decision making, and cognitive skill acquisition; he is an Assistant Professor in the Human Factors Division and Beckman Institute of Advanced Science and Technology at the University

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