Modeling Age-related Differences in Information Search

Abstract

A number of cognitive processes are involved in the process of information search: memory, attention, comprehension, problem solving, executive control and decision making. Several cognitive factors such as aging-related cognitive abilities in turn influence either positively or negatively the above cognitive processes. We argue that the traditional click models from information retrieval community that predict user clicks do not take into account the effects of aging. We propose to exploit the capabilities of computational cognitive models that can simulate the effects of cognitive factors on information search behavior. In this direction, we present some ideas to incorporate effects of aging into a computational cognitive model called CoLiDeS+. Preliminary analysis of our ideas on predicting individual differences due to aging effects show promising outcomes.