Investigating the relation between users' cognitive style and web navigation behavior with k-means clustering

Abstract

This paper focuses on modeling users' cognitive style based on a set of Web usage mining techniques on navigation patterns and clickstream data. Main aim is to investigate whether k-means clustering can group users of particular cognitive style using measures obtained from a series of psychometric tests and content navigation behavior. Three navigation metrics are proposed and used to find identifiable groups of users that have similar navigation patterns in relation to their cognitive style. The proposed work has been evaluated with a user study which entailed a psychometric-based method for extracting the users' cognitive styles, combined with a real usage scenario of users navigating in a controlled Web environment. A total of 22 participants of age between 20 and 25 participated in the reported study providing interesting insights with respect to cognitive styles and navigation behavior of users. © 2012 Springer-Verlag.