Proceedings of the Annual Meeting of the Cognitive Science Society

With the ever increasing amount of information available, the ability to prioritize the most relevant items for full processing is increasingly necessary to maintain expertise in a domain. As a result, accurate triage decisions--initial decisions about the relevance of a given article, book, or talk in order to determine whether to pursue that information further--are very important. In the present paper, we present a model of triage decision making that includes both an information search component to determine reading strategy and a decision making component to make the final decision. We apply the model to human relevance ratings as well as binary decisions of relevance for a set of emails.