predictive modeling of first-click behavior in web-search
Search engine results are usually presented in some form of text summary (e.g., document title, some snippets of the page's content, a URL, etc). Based on the information contained within these summaries users make relevance judgments about what links best suit their information needs. Current research suggests that these relevance judgments are in the service of some search strategy. In this paper, we model two different search strategies (the comparison and threshold strategies) and determine how well they fit data gathered from an experiment on user search within a simulated Google environment.
link analysis information scent empirical tests predictive user modeling web evolution information navigation search behavior